fetal hemodynamics and brain development in … fetal hemodynamics and brain development in late...
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Fetal Hemodynamics and Brain Development in Late Onset Intrauterine Growth Restriction
by
Meng Yuan Zhu
A thesis submitted in conformity with the requirements for the degree of Master of Science
Institute of Medical Science University of Toronto
© Copyright by Meng Yuan Zhu 2016
ii
Fetal Hemodynamics and Brain Development in Late Onset Intrauterine Growth Restriction
Meng Yuan Zhu
Master of Science
Institute of Medical Science
University of Toronto
2016
Abstract
Late-onset intrauterine growth restriction (IUGR) results from placental insufficiency. It has an
adverse impact on brain development. However, the relationships between placental function,
fetal hemodynamics and cerebral maturation in human IUGR are poorly understood. This thesis
describes our findings using MRI technology in late-onset IUGR. We measured key
hemodynamic parameters and compared them with indices of brain development in neonates
following late-onset IUGR. MRI revealed the expected adaptive responses to hypoxia in IUGR
fetuses. MRI parameters including flow in the superior vena cava and oxygen delivery could be
useful markers of late-onset IUGR. We also observed reduced cerebral oxygen delivery in
IUGR fetuses, which could be associated with reduced brain growth and delayed white matter
development. Preliminary data indicated that IUGR was impacting subsequent
neurodevelopmental outcomes. Our finding would suggest that MRI could provide useful
adjunct to current monitoring and help define the optimal timing of delivery of late-onset IUGR.
iii
Acknowledgments I would like to begin by thanking my supervisor, Dr. Mike Seed for giving me this opportunity
to work on this fascinating project. I greatly appreciate your guidance and patience throughout
the course of this project. You are always optimistic and supportive. Your encouragement and
confidence in my research skills have been invaluable to me.
Thank you to my advisory committee, Dr. Christopher Macgowan, Dr. John Kingdom, and Dr.
Brian McCrindle, for dedicating the time and effort to guide me through this project. You have
been always there to give timely help and advice. A sincere thank you to everyone who
contributed to the work: Dr. Sarah Keating, Dr. Rory Windrim, Dr. Johannes Keunen, Dr.
Varsha Thakur, Dr. Annnika Ohman, Dr. Sharon Portnoy, Dr. John Sled, Dr. Edmond Kelly, Dr.
Shi-Joon Yoo, Dr. Lars Gross-Wortmann and Dr. Edgar Jaeggi. Your expertise and suggestions
made the publication of this work possible.
It has been a great pleasure working in Dr. Seed’s lab, due in large part to my lovely lab mates:
Dr. Liqun Sun, Dr. Prashob Porayette, Dr. Sujana Madathil, Jessie Mei Lim, Brahmdeep Saini,
Angela Duan, Ioana Stochitoiu and Theo Kingdom, who have provided me with encouragement,
assistance and laughter. I also thank our study coordinator Natasha Milligan for all her patience
and support throughout the years and all the study subjects who volunteered their time to make
this project possible.
I also gratefully acknowledge the support from the Ontario Graduate Scholarship, my home
department Institute of Medical Science at the University of Toronto and The Hospital for Sick
Children.
Last but not least, thank you to my loving family for your continuing support. Without them, I
would not be where I am today. Thank you to my husband, Wesley Phuong, for enduring the
worst of me and practice talks with me until you can repeat my speech.
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Contributions The research presented in this thesis was adapted from Zhu, Meng Yuan et al. 2016. “The
hemodynamics of late-onset intrauterine growth restriction by MRI.” American Journal of
Obstetrics & Gynecology 214(3):367e1-e7. Permission of use was obtained from Journal.
The author performed all the data collection and analysis, with the guidance and expertise of the
individuals listed below:
Dr. Mike Seed and Ms. Navjot Gill: Performed Magnetic Resonance Imaging (MRI) scan on
fetal and newborn subjects.
Dr. John Kingdom: Provided guidance in data analysis on categorization of IUGR subjects
Dr. Christopher Macgowan: Helped with the understanding of the MRI protocol and the novel
gating technique used in the study (Metric Optimized Gating).
Dr. Prashob Porayette: Provided guidance on the fetal physiology and interpretation of
Magnetic Resonance (MR) images.
Dr. Liqun Sun and Dr. Sujana Madathil: Provided guidance with the utility of MRI post-
processing software.
Dr. Sarah Keating: Assessed placental pathology of normal and IUGR subjects in the cohort.
Ms. Natasha Milligan: Recruitment of normal and suspected IUGR subjects and scheduled
follow-up for newborn brain MRI scans.
Dr. Varsha Thakur and Dr. Annika Ohman: Performed ultrasound scan on subjects and
provided guidance in the interpretation of Doppler ultrasound parameters.
Dr. Edmond Kelly: Performed developmental follow-up of subjects.
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Table of Contents
Abstract……………………………………………………………………………………………………………………………….ii
Acknowledgments.................................................................................................................iii
Contributions........................................................................................................................iv
ListofTables........................................................................................................................vii
ListofFigures......................................................................................................................viii
ListofAppendices..................................................................................................................x
ListofAbbreviations..............................................................................................................xi
1 GeneralIntroduction.....................................................................................................1
1.1 Late-onsetIUGRandcurrentdiagnosis................................................................................3
1.1.1 IUGR.......................................................................................................................................3
1.1.2 Conventionalsonographyinlate-onsetIUGR......................................................................17
1.1.3 MRIinfetalstudies..............................................................................................................31
1.2 NeurodevelopmentinIUGRandbrainMRI.......................................................................42
1.2.1 CerebraloxygenationandneurodevelopmentinIUGR.......................................................42
1.2.2 BrainMRI.............................................................................................................................45
2 RationaleandResearchObjectives...............................................................................52
3 Methods.......................................................................................................................56
3.1 Participants.......................................................................................................................56
3.2 Fetalhemodynamicassessment........................................................................................57
3.2.1 MRIprotocolinfetalstudy..................................................................................................57
3.2.2 Doppler(UAandMCA)........................................................................................................62
3.2.3 IUGRdiagnosis.....................................................................................................................62
3.3 Neurodevelopmentinlate-onsetIUGR..............................................................................64
3.3.1 NewbornBrainMRI.............................................................................................................64
3.3.2 Developmentalassessment.................................................................................................65
3.4 Statisticalmethods...........................................................................................................66
4 Results..........................................................................................................................68
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4.1 Participants.......................................................................................................................68
4.2 FetalhemodynamicbyMRIandultrasound......................................................................72
4.2.1 Imagingresults....................................................................................................................72
4.2.2 Placentalhistology...............................................................................................................79
4.2.3 Correlations.......................................................................................................................80
4.2.4 PerformanceofMRIandDoppler........................................................................................85
4.3 Neurodevelopmentinlate-onsetIUGR..............................................................................87
4.3.1 Fetalbrainoxygenation.......................................................................................................87
4.3.2 NeonatalbrainMRI.............................................................................................................88
4.3.3 Developmentalfollow-up....................................................................................................92
5 Discussion.....................................................................................................................94
5.1 IUGRhemodynamicandoxygenation...............................................................................95
5.1.1 Comparisonwithgrowthrestrictionincongenitalheartblock...........................................97
5.1.2 UltrasoundandMRIinIUGRdetection...............................................................................98
5.2 Neurodevelopmentinlate-onsetIUGRandfurtherthoughts..........................................101
5.3 Limitations......................................................................................................................103
5.3.1 DiagnosisofIUGR..............................................................................................................103
5.3.2 AccuracyofMRItechnique................................................................................................105
6 Conclusion..................................................................................................................108
7 Futuredirections........................................................................................................109
7.1.1 T1andT2Calibrationforhematocritandoxygensaturation............................................110
7.1.2 PlacentalfunctionbyMRI..................................................................................................111
References.........................................................................................................................113
Appendices........................................................................................................................126
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List of Tables Table 1. MRI sequence protocol.. ............................................................................................... 58
Table 2. Newborn brain MRI protocol. ....................................................................................... 65
Table 3. Delivery condition of the 14 IUGR subjects.. ............................................................... 70
Table 4. Characteristics of normal and IUGR group.. ................................................................ 71
Table 5. Doppler ultrasound findings in normal and IUGR fetuses. ........................................... 79
Table 6. Developmental outcome in IUGR and normal infants. ................................................. 93
viii
List of Figures Figure 1 Placental circulation in normal and utero-placental vascular insufficient pregnancies .. 5
Figure 2 Example of a normal and an IUGR placenta. ................................................................. 7
Figure 3 Streaming patterns in the fetal circulation in response to variations in placental oxygen
delivery ................................................................................................................................ 10
Figure 4 Ultrasound features of normal, early-onset IUGR and late-onset IUGR pregnancies . 18
Figure 5 Example of normal and abnormal umbilical artery Doppler ........................................ 26
Figure 6 Example of middle cerebral artery Doppler in a normal and an IUGR fetus ............... 28
Figure 7 Example of fetal body and brain segmentation from SSFP sequence .......................... 34
Figure 8 Example of T2 mapping ............................................................................................... 42
Figure 9 Example of newborn brain Diffusion Weighted Imaging ............................................ 47
Figure 10 Example of newborn brain Diffusion Tensor Imaging ............................................... 49
Figure 11 Flow diagram of the study participants in the study ................................................... 69
Figure 12 Estimated fetal weight measured by MRI and ultrasound .......................................... 73
Figure 13 Comparison of head circumference / birth weight ratio between IUGR and normal
newborns .............................................................................................................................. 73
Figure 14 MRI measured major vessel flows in the IUGR and normal fetuses ........................ 75
Figure 15 T2 relaxation time in major vessels in normal and IUGR fetuses .............................. 77
Figure 16 Calculated oxygen consumption and oxygen delivery in IUGR and normal fetuses 77
Figure 17 The association of IUGR score with Doppler parameters. ......................................... 80
Figure 18 The association of IUGR score with MRI parameters ............................................... 81
ix
Figure 19 Association of brain weight with CPR and SVC flow ............................................... 82
Figure 20 Association between T2 in the umbilical venous blood with blood flow in the SVC.
.............................................................................................................................................. 83
Figure 21 Association between CPR and blood flow in the SVC. MRI-measured SVC flow and
CPR were negatively correlated. .......................................................................................... 84
Figure 22 Association between oxygen delivery and UA PI. Calculated DO2 was negatively
associated with UA PI. ......................................................................................................... 84
Figure 23 ROC curves for MRI and Doppler measurements for identification of IUGR .......... 87
Figure 24 Cerebral oxygen consumption and cerebral oxygen delivery in normal and IUGR
newborns .............................................................................................................................. 88
Figure 25 Brain weight Z-score in IUGR and normal newborns ................................................ 89
Figure 26 Association of FA and ADC in thalamus and anterior white matter with corrected
gestational age ...................................................................................................................... 90
Figure 27 Fractional anisotropy in white matter and basal ganglia in normal and IUGR
newborns .............................................................................................................................. 91
Figure 28 Association between net fetal cerebral oxygen deliver and neonatal brain weight Z-
score ..................................................................................................................................... 91
Figure 29 Postnatal anthropometric indices in IUGR and control subjects ................................ 92
x
List of Appendices Appendix I. Validation of flow measurements.
Appendix II. Validation of T2 measurements.
Appendix III. Validation of phase contrast pulmonary blood flow measurements.
Appendix IV. Comparison of T2 versus SaO2 between umbilical cord blood and adult blood
with Hct = 0.47 (Portnoy et al., 2015)
xi
List of Abbreviations
AAo ascending aorta
ADC apparent diffusion coefficient
AGA appropriate for gestational age
CDO2 cerebral oxygen delivery
CPR cerebroplacental ratio
CVO combined ventricular output
CVO2 cerebral oxygen consumption
DA ductus arteriosus
DAo descending aorta
DO2 oxygen delivery
EBW estimated brain weight
EFW estimated fetal weight
FA fractional anisotropy
GA gestational age
IUGR intrauterine Growth Restriction
MCA middle cerebral artery
MOG metric optimized gating
MRI magnetic resonance Imaging
MRS magnetic resonance spectroscopy
OEF oxygen extraction fraction
PI pulsatility index
SaO2 oxygen saturation
SGA small for gestational age
SVC superior vena cava
UA umbilical artery
UV umbilical vein
VO2 oxygen consumption
1
1 General Introduction Intrauterine growth restriction (IUGR) is associated with perinatal mortality and
significant morbidity of surviving newborns. It is characterized by the failure of the fetus to
reach its genetic growth potential (Figueras & Gardosi, 2011). IUGR affects up to 10% of
pregnancies in Canada and the majority of these cases are the result of placental insufficiency
(Lausman & Kingdom, 2013). Recent studies have shown that several factors can contribute to
IUGR, including smoking, gestational hypertension and malnutrition (Romo et al., 2009).
IUGR is associated with an increased risk of stillbirth, adverse perinatal outcomes (Von
Beckerath et al., 2013; Lausman & Kingdom, 2013), and neurodevelopmental delay (Arcangeli
et al., 2012; Eixarch, 2008; Von Beckerath et al., 2013). IUGR cases that develop earlier than 32
weeks’ gestation are usually managed conservatively because the complications of premature
birth outweigh the potential benefit of delivery from a hypoxic and undernourished fetal
environment (Figueras & Gardosi, 2011). Early-onset IUGR cases are easily detected using
conventional Doppler ultrasound and medical delivery is indicated to prevent stillbirth in the
setting of deteriorating cardiac function. In cases where IUGR develops after 34 weeks’
gestation (known as late-onset IUGR), the morbidity associated with preterm birth is much less
significant. However, if the condition goes unnoticed, it can also result in adverse outcomes
such as a compromised neonatal condition with long-term implications for neurodevelopment. It
has been hypothesized that timely delivery of late-onset IUGR fetuses from an unhealthy in-
utero environment may avoid suboptimal perinatal outcomes (Lausman & Kingdom, 2013).
However, conventional Doppler ultrasound markers of placental insufficiency, particularly the
increase in umbilical artery pulsatility typical of early-onset IUGR, are frequently absent in the
late-onset form of the disease. Physiological adaptation associated with chronic hypoxia that
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occurs in the third trimester may help explain the limitations of conventional Doppler measures
and ultrasound to detect late-onset IUGR. For example, animal studies indicate that the Doppler
changes seen in acute hypoxia may pseudo-normalize in chronic fetal hypoxia as fetal metabolic
adaptation downregulates the fetal requirement for oxygen (Pearce, 2006; Richardson &
Bocking, 1998; Poudel et al., 2015). Furthermore, ultrasound-based fetal weight estimation can
be hindered by oligohydramnios, which is often associated with late-onset IUGR. As a result,
detection rates for late-onset IUGR are currently low, while false positives may be present in
30% of cases (Backe & Nakling, 1993; Boers et al., 2010). The result is a high incidence of
unnecessary iatrogentic late preterm birth and unacceptably high rates of late gestational
stillbirth and perinatal brain injury (Gardosi et al., 2013). These limitations highlight the need to
develop better clinical measures and tools to detect late-onset IUGR.
This study consists of two components. In the first part of the study, we investigated the
fetal hemodynamic adaptation to late-onset IUGR using MRI. The performance of MRI
technology in detecting late-onset IUGR was compared with conventional ultrasound using
placental histology and neonatal anthropometric measurements as our gold standard for IUGR
diagnosis. In the second part of the study, we investigated the impact of late-onset IUGR on
neurodevelopment using quantitative MRI measures of brain development at birth, and
functional testing during the first 18 postnatal months. Our ultimate goal is to provide an
improved understanding of the relationships between placental function, fetal cerebral
hemodynamics and metabolic adaption and brain growth and development in the setting of late-
onset IUGR. We hope that this information may prove helpful to perinatalogists as they strive
to determine the optimal timing of delivery from a neurodevelopmental perspective in this
common condition.
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1.1 Late-onset IUGR and current diagnosis
1.1.1 IUGR
The term “small for gestational age” (SGA) has been used interchangeably with IUGR.
However, it is important to discriminate between SGA and IUGR. SGA describes fetuses with
estimated fetal weights (EFW) below the 10th percentile for the appropriate gestational age,
which simply describes a low fetal weight; whereas IUGR describes the situation when a fetus
fails to reach its growth potential due to deficiencies in the placental supply of oxygen and
nutrition. The smallness of a fetus can result from genetic disposition rather than pathological
growth restriction. It has been shown that failure to discriminate between SGA and true IUGR
results in a high false positive rate for IUGR, as many SGA fetuses are constitutionally small
and not affected by IUGR (Boer et al., 2010). On the other hand, fetuses that are ‘Appropriate
for Gestational Age’ (AGA), who have EFW above the 10th centile may be growth restricted
(Deter & Spence, 2004).
IUGR has two presentations, early- and late-onset (Lausman & Kingdom, 2013). Early-
onset IUGR presents during the second trimester of pregnancy, and is usually associated with
abnormal placental growth and development. Additional causes of early onset IUGR include
fetal infections and/or a genetic disorder of the fetus (Grivell et al., 2009). Early-onset IUGR is
usually more severe than late-onset IUGR and nearly always associated with the fetus being
small for gestational age. Early-onset IUGR can therefore be easily identified using
conventional ultrasound to assess fetal growth. High placental vascular resistance resulting
from abnormal placentation is also a frequent feature of early-onset IUGR and so the
combination of fetal biometry and umbilical artery Doppler are reliable for diagnosis (Figueras
& Gardosi, 2010).
4
Late-onset IUGR occurs after 34 weeks’ gestation, and is the more common form of the
condition (Figueras & Gardosi, 2010). The most frequent etiology of late-onset IUGR is
placental dysfunction, which may be associated with maternal malnutrition and substance abuse.
In late-onset IUGR cases, placental supply fails to keep up with the increasing demands for
nutrients and oxygen in the rapidly growing late gestation fetus. In early-onset IUGR, the
neonates are almost always SGA. However, in up to 50% of late-onset IUGR fetuses, the EFW
remains above the 10th percentile, because of the late onset of the condition (Sifianou, 2010). In
the absence of serial measures of fetal growth, fetal biometry may therefore be falsely
reassuring. Moreover, late-onset IUGR is not always associated with abnormalities of
conventional Doppler parameters (Oros, 2011). Therefore, many late-onset IUGR cases go
unnoticed by current fetal monitoring regimes. Although late-onset IUGR is the milder form of
fetal growth restriction, failure to identify placental insufficiency occurring at the end of the
pregnancy may nevertheless be of clinical significance, as even this form of IUGR is associated
with an increased risk of stillbirth and neonatal complications.
1.1.1.1 Role of the placenta
Placental insufficiency is the main cause of late-onset IUGR. The placenta connects the
developing fetus to the uterine wall and functions to provide oxygen and nutrients from the
mother to the fetus via uterine arteries and removes waste product from fetal blood. The
relatively high pressure from uterine blood flow fills the intervillous space of the placenta and
bathes fetal villi in blood. This allows oxygen and nutrients to pass on to the fetal blood as well
as enter fetal circulation via the umbilical vein (Scifres & Nelson., 2009) (Figure 1a). Uterine
blood flow increases with advancing gestation. On the fetal side, deoxygenated fetal blood flows
towards the placenta through umbilical arteries. Typically, during the late stages of gestation,
physiological changes occur to optimize the exchange of gas and substrates from the mother to
5
the fetus. The placenta has low blood flow resistance to allow perfusion of maternal blood flow
into intervillous space and umbilical arteries (Scifres & Nelson., 2009). Due to this special role
of the placenta, abnormal placentation or pathological changes in the placenta will have a
deleterious effect on maternal and fetal health, such as the development of pre-eclampsia and
IUGR.
Figure 1 Placental circulation in normal and utero-placental vascular insufficient
pregnancies. a) placental circulation in normal pregnancy. b) placental circulation when there is
utero-placental vascular insufficiency.
The majority of IUGR cases are associated with placental lesions. This was established
by Salafia et al. (1992), who investigated placental pathology in 128 IUGR cases and 179
gestational age-matched normal placentas. The typical placental lesions include: infarction,
chronic villitis, hemorrhagic endovasculitis and placental vascular thrombosis. One or more of
the lesions were present in 55% of IUGR cases, which is significantly higher than in the non-
IUGR cases (32%). IUGR pregnancies tend to have multiple types of lesions in the placenta
(Salafia et al., 1992). In keeping with Salafia et al., Redline (2008) demonstrated five patterns of
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placental injury that are associated with pregnancies complicated by IUGR, including maternal
and fetal vascular obstruction, high-grade villitis, perivillous fibrin deposition and chronic
abruption. Fetal growth is also affected by the condition of the umbilical cord, which connects
the placenta to the fetus. Peyter et al. (2013) illustrated that growth restricted fetuses had lower
placental weight as well as altered structure and function of the umbilical cord. In combination,
these lesions lead to an increase in the vascular resistance of the placenta (Figure 1b).
However, the clinical presentation of late-onset IUGR is associated with milder forms of
placental lesions (Kovo et al., 2013). Late-onset IUGR may be characterized by a combination
of fetal and maternal vascular compromise rather than the more severe vascular lesions reported
in early-onset IUGR cases. In late-onset IUGR cases, placental injuries may have minor effects
on fetal growth at the beginning of gestation. However, as the fetus grows, the lesions become
deleterious to fetal development. Eventually, the placenta will not be able to keep up with the
increasing demand for nutrients and oxygen (particularly in the third trimester of pregnancy)
and the development of fetal hypoxia results in a slowing of fetal growth. Because most of the
placental lesions associated with late-onset IUGR are mild, this condition is often associated
with an absence of abnormal umbilical artery flow patterns (Oros et al., 2011). Therefore,
instead of direct assessment of placental flow resistance, the diagnosis of late-onset IUGR relies
on the detection of physiological adaptations to placental dysfunction by the fetus. For example,
adopting the Doppler waveform to measure blood flow in the middle cerebral artery (MCA)
may be applied as an indicator of an adaptive phenomenon called “brain-sparing” physiology.
7
Figure 2 Example of a normal and an IUGR placenta. a) A normal placenta is round shaped
with central insertion of the cord. b) An abnormal placenta with marginal insertion of the cord.
1.1.1.2 Physiological adaptations in late-onset IUGR
Late-onset IUGR is associated with fetal hypoxemia. This has been demonstrated in
realistic animal models of human IUGR. In a fetal sheep carunclectomy model, Poudel et al.
(2015) observed that fetal arterial oxygen saturations are approximately half their normal values
in IUGR fetuses. The association between IUGR and hypoxemia has also been confirmed by
cordocentesis in human IUGR pregnancies (Hecher et al., 1995). Current identification of late-
onset IUGR relies on the detection of hemodynamic adaptations to hypoxemia, which appears to
be a universal feature of IUGR.
Hypoxia has profound effects on metabolism and growth. Oxygen level is closely
monitored to ensure viability and function at both the cellular and organismal levels. When there
is oxygen deprivation, adaptive responses that coordinate the demand and supply mismatch can
develop to minimize the adverse effect caused by hypoxia.
At a cellular level, oxygen is essential for various metabolic activities such as RNA
translation and cell growth. One of the major oxygen consuming processes is mitochondrial
biogenesis or cellular respiration that produces biochemical energy from nutrients and oxygen.
a) b)
8
Hypoxic conditions can lead to energy starvation, and inhibit protein synthesis through various
pathways, which ultimately disrupt the growth and proliferation of cells (Liu et al., 2006). This
could be an explanation of the association between hypoxemia and restricted growth in IUGR
fetuses. Cellular respiratory rates are normally determined by the activity of metabolism.
However, when oxygen is limited, cells are able to reduce the rate of respiration (Liu et al.,
2006). Reducing cellular respiration as oxygen delivery diminishes could delay the onset of
tissue anoxia and limit the production of harmful reactive oxygen species (Wheaton & Chandel,
2011). Therefore, this adaptive mechanism helps prevent tissue injury under oxygen deprivation
(Wheaton & Chandel, 2011). In addition, cells can reduce metabolic activity and energy demand
to confer an increased resistance to the diminished oxygen supply (Schumacker et al., 1993).
This phenomenon is referred to as oxygen conformance (Schumacker et al., 1993). For example,
in 1986, Hochachaka showed that decreased oxygen delivery in myocardium resulted in
diminished contractile function, therefore decreased oxygen demand. Selective inhibition of
metabolic activities allows cells to preserve limited energy production for functions necessary
for cell survival. It has been shown that although the oxygen suppression caused by chronic
hypoxia was reversible and did not result in detectable cell injury, it significantly reduced cell
size (Liu et al., 2006). Therefore, the downregulation of both the energy production and oxygen
demand during hypoxia help maintain homeostasis and prevent damage to the tissue is at the
expense of other metabolic processes (Wheaton & Chandel, 2011). Due to this cellular
adaptation mechanism, reduced oxygen delivery to IUGR fetal tissue would ultimately lead to
reduced oxygen demand over time at the expense of slowing down of growth.
At the level of fetuses, they are also able to adapt to in utero hypoxemia through various
mechanisms. In 1974, Cohn et al. investigated the circulatory responses to acute hypoxemia in
fetal lambs (Cohn et al., 1974). The authors altered the oxygen content of the maternal ewe’s
9
inspired air to create maternal hypoxia. To avoid maternal hyperventilation, a consistent
decrease in fetal arterial oxygen saturation was achieved without significant changes in the
maternal partial pressure of carbon dioxide. Fetal cardiac output and flow distribution were
measured invasively by nuclide-labeled microspheres. The investigators observed that in the
hypoxia group without acidemia, cardiac output was slightly decreased and umbilical blood
flow was maintained. As a result, the distribution of the cardiac output to the placenta was
slightly increased. In addition, blood flow to the brain, heart and adrenal glands rose two to
three fold whereas blood flow to the pulmonary, renal and gut circulations significantly
decreased (Cohn et al., 1974). Similar circulatory redistribution patterns were subsequently
observed in other sheep models of placental dysfunction (Peeters et al., 1979).
Such dramatic redistribution of blood flow across the circulation is unique to the fetus
and is made possible by the presence of connections between the systemic and pulmonary
circulations. The ductus venosus connects the portal vein to the inferior vena cava, which allows
blood returning from the placenta to bypass the liver. The foramen ovale allows flow of blood
between the atriums and the ductus arteriosus connects the main pulmonary artery to the aorta.
10
Figure 3 Streaming patterns in the fetal circulation in response to variations in placental
oxygen delivery. In the setting of reduced placental function (right) ascending aortic flow is
maintained at the same oxygen saturation as in the average situation (middle) at the expense of
the rest of the circulation by a large foramen ovale shunt and vasoconstricted pulmonary
circulation.
As shown in Figure 3, when there is a reduction in oxygen supply from the placenta, the
ductus venosus is able to redirect a larger proportion of the oxygenated umbilical venous return
away from the liver and towards the foramen ovale (Kiserud et al., 2006). Both the foramen
ovale and ductus arteriosus shunt blood away from the lungs, which is tolerated in the fetus
because the lungs are not being used for gas exchange. When fetal oxygen saturations are low,
pulmonary vascular resistance increases (Cohn et al., 1974; Peeters et al., 1979; Rurak et al.,
1990). As a result, pulmonary venous return is diminished and there is an increase in foramen
ovale shunting. A reduction in impendence in the cerebral circulation functions to maintain the
11
supply of oxygen and nutrients to the brain. This physiological adaptation to hypoxia is known
as the “brain-sparing effect”, and can be detected by abnormal Doppler waveforms in the MCA.
“Brain-sparing” is both protective and potentially pathologic because the neuroprotective effect
is at the expense of other fetal organs and body growth (Rurak et al., 1990). For example,
increased shunting at the ductus venosus would affect the biosynthesis of fetal proteins that are
predominantly produced by the liver. Impaired protein biosynthesis will lead to impaired fetal
growth (Kaponis et al., 2011). Chronic redistribution of the oxygenated blood in the fetal
circulation will therefore lead to asymmetric growth restriction that is characterized by a
disproportionately large head size of the fetus relative to their body size and a decrease in fetal
subcutaneous fat (Baschat, 2011).
Although placental insufficiency directly affects oxygen delivery to the fetus, it has been
shown that the total fetal oxygen consumption could remain unchanged with up to 50% acute
reduction in oxygen delivery (Rurak et al., 1990). This is achieved by increasing fractional
oxygen extraction with a larger oxygen partial pressure difference between the umbilical artery
and umbilical vein (Rurak et al., 1990). The degree to which oxygen extraction fraction can
increase and fetal arterial oxygen can decrease before altering oxygen consumption is difficult
to establish in human fetuses (Richardson & Bocking, 1998). However, it is known that the
compensatory mechanism would eventually fail in the setting of more profound oxygen
desaturation of umbilical venous blood. In fetal sheep, Yaffe et al. (1987) created a model of
placental dysfunction by chronically occluding blood flow in the uterine artery. Changes in fetal
blood gas, heart rate and regional distribution of blood flow under different levels of uterine
artery blood flow were measured. As expected, a progressive reduction of uterine blood flow
was associated with an increased degree of fetal hypoxemia. The investigators reported that
under a moderate level of hypoxemia, blood flow was redistributed to the heart, brain and
12
adrenal gland, which is consistent with what Cohn et al. (1974) had shown. However, exposure
to more severe fetal hypoxemia (when uterine blood flow was reduced to 25%) was associated
with a reduction of fetal blood flow in all organs. Moreover, a prolonged reduction in fetal
oxygen delivery over several days was not associated with elevated oxygen extraction. The
authors concluded that fetal oxygen consumption was positively correlated with oxygen delivery
in severe chronic fetal hypoxia (r = 0.8, P < 0.001) (Anderson et al., 1986). Taken together, it is
evident that the physiological adaptation of acute versus chronic fetal exposure to hypoxia
differs. In prolonged late-onset IUGR, chronic fetal hypoxia would therefore be expected to
result in reduced fetal oxygen consumption, which could be attributed to a range of mechanisms
including cessation of growth and diminished activity. Consequently, a reduction in fetal brain
metabolism and cerebral blood flow will eventually dampen the “brain-sparing” effect
(Richardson & Bocking, 1998). Studies have also shown that with sustained hypoxemia, fetal
hemoglobin concentration increases, which could also contribute to the resolution of cerebral
vasodilation through an increase in the oxygen carrying capacity of the blood supplied the brain.
Few studies have investigated the relationship between cerebral oxygen delivery and brain
development in utero, as we have traditionally lacked methods to measure fetal cerebral oxygen
delivery in animals and humans. However, regardless of how cerebral oxygen delivery is
affected by IUGR, animal models of placental insufficiency show that brain development is
affected. While numbers of neurons appear to be preserved, dendritic arborization appears to be
diminished, and white matter myelination is delayed (Rees et al., 2005; Tolcos et al., 2011).
While there is some evidence for post-natal catch up growth of brain structures in animals and
humans (Tolcos et al., 2011; De Wit CC et al, 2013), it has been proposed that impaired brain
growth and development due to chronic adaptation to fetal hypoxia may result in subsequent
adverse neurodevelopmental outcomes for the child (Baschat, 2011).
13
1.1.1.3 Adverse outcomes in IUGR
Significant morbidity and mortality is associated with IUGR pregnancies. Various
studies investigating the perinatal outcome of IUGR pregnancies have reported that SGA and
IUGR pregnancies are associated with a higher rate of stillbirth (Moraitis et al., 2014; Allen et
al., 2016); higher rate of admission to neonatal intensive care units (Flood et al., 2014; Oros et
al., 2014); higher need for emergency cesarean section (Severi et al., 2002; Flood et al., 2014);
and higher rates of respiratory distress and lower Apgar scores (Baschat et al., 2000; Flood et
al., 2014).
In addition to the adverse perinatal outcomes that are associated with IUGR, there are
also studies that have reported adverse long-term outcomes that result from chronic fetal blood
flow redistribution. The adaptive redistribution of fetal blood flow in IUGR has been associated
with cardiovascular disease and hypertension. Hecher et al. (1995) demonstrated that IUGR
fetuses had cardiac systolic and diastolic dysfunction. This finding is further supported by a
recent study with nine severe IUGR cases and nine AGA fetuses who died in the perinatal
period due to termination of pregnancy because of severe maternal disease or non-cardiac
malformations (Iruretagoyena et al., 2014). Echocardiographic results and biochemical markers
taken before delivery or death showed signs of severe cardiac dysfunction in IUGR fetuses. The
molecular changes in these cardiac myocytes were analogous to those in dilated cardiomyopathy
and diastolic heart failure. These lesions were similar to cardiac remodeling associated with
sustained pressure and volume overload (Iruretagoyena et al., 2014). These findings are
consistent with observational studies, that reported an association between low birth weight and
increased risk of death from heart disease in adults (Demicheva & Crispi, 2014).
14
The redistribution of oxygenated blood to the brain and heart in response to IUGR is at
the expense of healthy development of other fetal organs. Many human studies have revealed an
association between low birth weight and hypertension in infants and adulthood, which is
thought to be associated with kidney function (Launer et al., 1993; Taylor et al., 1997). Since
the kidney plays a crucial role in the regulation of blood pressure, it has been proposed that the
association of IUGR and hypertension could be attributed to impaired renal function caused by
reduction in nephron number as demonstrated in both animal models and stillbirth human
fetuses (Luyckx & Brenner, 2005; Ortiz et al., 2001; Hinchliffe et al., 1992).
IUGR can also cause metabolic disturbances and result in adult diseases such as diabetes
mellitus and obesity (Wang et al., 2016). There is also emerging evidence showing that growth
restriction severely affects brain development, short- and long-term brain functions in fetus and
infants (Wang et al., 2016). This will be discussed in detail in section 1.2.
1.1.1.4 Timing of delivery in late-onset IUGR
It is hoped that better techniques to detect late-onset IUGR will help us identify a
window of opportunity for clinical intervention in order to optimize the perinatal and
developmental outcomes of babies affected by late-onset IUGR. Various studies that have
assessed the usefulness of potential treatment options such as low dose Aspirin and maternal
oxygenation did not show any convincing benefit in terms of birth weight or extending birth
gestational age in IUGR fetuses (McCowan et al., 1999; Lausman & Kingdom, 2013).
Therefore, determining the optimal time for delivery remains the principle management
challenge in the setting of IUGR. Earlier delivery from an unfavorable in-utero condition could
avert some of the adverse outcomes associated with IUGR. However, there are also risks related
to late preterm birth. Escobar et al. (2006) reported that infants born at 35 and 36 weeks’
15
gestation had considerable mortality and morbidity. These babies had almost three times higher
rate of respiratory stress compared to infants born at or after 37 weeks’ gestation. Also, late-
preterm infants were more likely to be re-hospitalized than term infants (Escobar et al., 2006).
Therefore, the decision about appropriate timing of delivery should weigh up the relative risks
of potential morbidity associated with late-preterm birth against those resulting from continued
exposure to an unhealthy in-utero environment. To date, attempts to investigate the effect of
modifying the timing of delivery have not shown a convincing benefit for earlier versus later
delivery. The Growth Restriction Intervention Trial (GRIT) (2004) was a large randomized
controlled trial that assessed the survival and long-term neurological outcome of early elective
delivery compared against delayed delivery in early-onset IUGR pregnancies. The study showed
no difference in short-term outcome with immediate delivery compared to more conservative
management. Subsequent infant developmental assessments at two years indicated no difference
between the two groups, although the group that had immediate delivery before 31 weeks’
gestation had a higher rate of severe disability (Walker et al., 2010). The conclusion of the study
was that the timing of delivery had little impact on long-term neurodevelopment; therefore, it
was safe to wait, especially before 36 weeks’ gestation. However, the study findings are of
limited relevance to late-onset IUGR and may have been influenced by selection bias, with less
severe cases, in which it would be safe to wait, more likely to be recruited. It has been suggested
that the selected group for the GRIT study may therefore not be representative of the majority of
IUGR cases (Figueras & Gardosi, 2010).
More relevant to late-onset IUGR, the Disproportionate Intrauterine Growth Intervention
Trial at Term (DIGITAT) (2010) compared the short-term outcomes of induced labor to the
outcomes of expectant monitoring for fetuses with suspected late-onset IUGR. In this
multicenter randomized trial, 650 singleton pregnancies with suspected IUGR beyond 36 weeks’
16
gestation were recruited. Suspected IUGR was defined as fetal abdominal circumference below
the 10th percentile, EFW below the 10th percentile or flattening of the growth curve in the third
trimester. On average, fetuses in the induced labour group were delivered ten days earlier and
weighed 130g less compared to those in the expectant monitoring group. There was no
difference in adverse neonatal outcome (including death, 5 min Apgar < 7; umbilical artery pH
< 7.05 or admission to intensive care unit) between the induction group and the expectant
monitoring group (5.3% vs 6.1%; 95% CI of difference: -4.3% to 3.2%). Early induction did not
appear to increase the rate of cesarean section (Boer et al., 2010). In a subsequent
neurodevelopmental follow-up study, parents of children in the study were asked to complete
questionnaires designed to detect developmental delay and behavioral problems. The authors
reported that the results of the developmental outcome were comparable between the two
groups. However, they also showed that severely growth restricted fetuses with birth weight less
than the 3rd centile performed worse in their developmental tests at two years of age. Therefore,
it was concluded that severe growth restriction remains the most important predictor of
abnormal developmental outcome at two years of age, and that neither induction of labor nor
expectant management had a difference in short- or long-term outcomes in suspected IUGR
pregnancies (van Wyk et al., 2012). There are limitations in this study that need to be considered
when interpreting the study results. For example, although fetuses with both normal and
abnormal UA Doppler were included in the study (both groups had similar UA Doppler
parameters), the fetal monitoring did not include assessment of the MCA Doppler, which has
been shown to be a more accurate indicator of the presence of IUGR than umbilical artery
Doppler in late pregnancy (Hershkovitz et al., 2000; Severi et al., 2002; Oros et al., 2011).
These limitations may contribute to the 30% false positive diagnosis of IUGR reported by the
DIGITAT study. This study nicely illustrates the challenges of accurate diagnosis of late-onset
17
IUGR and that improved techniques for discriminating between SGA and late-onset IUGR are
needed.
1.1.2 Conventional sonography in late-onset IUGR
Current monitoring of pregnancies largely relies on non-invasive obstetric ultrasound.
Ultrasound uses the properties of acoustic physics to localize and characterize different types of
tissue. The sound waves have frequencies that are higher than those audible to human. During a
scan, an ultrasound transducer sends ultrasound pulses into tissue and then receives the echoes
that come back. Different tissue reflects varying degrees of sound. The echoes that contain
spatial and contrast information about the tissue are then recorded and displayed as images
(Kremkau, 2011). Ultrasound can provide information about fetal well-being from different
aspects including assessments of fetal growth rate and blood flow waveforms in major fetal
vessels. Figure 4 summarized some conventionally used ultrasound features in normal, early-
onset IUGR and late-onset IUGR pregnancies. Details about the ultrasound parameters are
introduced below.
a)
18
Figure 4 Ultrasound features of a) normal, b) early-onset IUGR and c) late-onset IUGR
pregnancies. Normal, early-onset IUGR and late-onset IUGR pregnancies have different
features of blood flow in fetal and maternal vessels and different patterns of fetal growth.
1.1.2.1 Biometry
During the past 40 years, ultrasound-based assessment of fetal biometry has become
routine practice in obstetrics and plays an important role in the decision-making process
regarding the timing of delivery (Nahum & Stanislaw, 2003). An accurate estimation of fetal
gestational age is a crucial aspect of the pregnancy especially in assessments of fetal growth and
decision-making on pregnancy management. Crown-rump length is a measure of the fetus from
the head to the buttocks, which is used to estimate the gestational age (Ohuma et al., 2013).
Studies have shown that the estimation of gestational age based on crown-rump length is more
reliable than calculations based on the first day of the last menstrual period (Mongelli et al.,
1996). Systematic use of ultrasound for pregnancy dating has been shown to reduce the rate of
post-term pregnancies. This reduced unnecessary interventions and improved identification of
post-term pregnancies, which are at risk of complications (Caughey et al., 2008).
b) c)
19
Ultrasonographic fetal biometry is also routinely performed to estimate fetal weight.
Several equations have been developed to mathematically calculate EFW. Among these,
Hadlock’s formula has been shown to be the most accurate and is widely accepted and
commonly used (Pinette et al., 1999). Hadlock’s formula was established based on 167 live-born
fetuses examined within one week of delivery. It is a regression model based on measurements
of fetal biparietal diameter, abdominal circumference and femur length (Hadlock et al., 1984).
In 2013, Oliver et al. (2013) evaluated the accuracy of the Hadlock equation in 709 women who
underwent ultrasound examination within 8 weeks of delivery. They showed that the Hadlock
equation only had -0.47% systematic error for scans within 2 weeks of delivery. This highlights
a very small margin error with the correct application of the Hadlock method.
Even though several studies have proved the reliability of Hadlock’s formula (Edwards
et al., 2001; Dudley, 2005), the accuracy of the estimation diminishes as the interval between
testing and delivery increases (Oliver et al., 2013). Moreover, the absolute error of the method
tends to increase with higher birth weight regardless of the interval between ultrasound exam
and delivery (Oliver et al., 2013). In addition, ultrasound-based fetal weight estimation can be
hindered by a low level of amniotic fluid and maternal obesity. The accuracy of Hadlock’s
estimation could also be reduced in asymmetrically grown fetuses such as IUGR fetuses who
have “brain-sparing” (Chang et al., 1992). It has been reported that a low abdominal
circumference of the fetus is more sensitive than EFW for detecting IUGR (Chang et al. 1992).
Alternatively, it has been shown that measures of fetal weight taken from serial ultrasounds to
plot growth rate reliably identify IUGR (Lausman & Kingdom, 2013). However, if the interval
between the serial ultrasound scans are less than two weeks apart, the estimation may not be
reliable (Mongelli et al., 1998). The common limitation of these ultrasonographic approaches is
that none of them directly measures the fetal volume or fetal weight. Moreover, weight
20
estimation should be combined with other indicators of compromised fetal condition in order to
identify IUGR, because small fetuses are not necessarily growth restricted, as discussed earlier.
1.1.2.2 Doppler
SGA is not equivalent to IUGR; therefore, in addition to fetal growth assessment,
Doppler ultrasound, which allows detection of hemodynamic adaptation to fetal hypoxia, serves
as an invaluable tool in the assessment of fetal well-being. Doppler ultrasonography utilizes the
Doppler principle, which states that the frequency of the echo reflected from a target is different
from the incident frequency (Atkinson and Wells, 1977). During a Doppler ultrasound scan, a
series of pulses are sent in order to detect the movement of fluid, such as blood. Stationary
tissues give the same echo from time to time, whereas echoes from flowing blood have slight
differences in the time it takes for the signal to be returned to the transducer (Atkinson and
Wells, 1977). The differences can be detected as direct time differences or a change in
frequency due to the velocity of the blood. They provide information to determine whether the
blood is moving away or towards the transducer and also about the velocity of the flow
(Atkinson and Wells, 1977). By convention, echoes from flows toward the transducer are
displayed as red, and flows away from the transducer are blue; Doppler frequency increases as
the blood velocity increases (Atkinson and Wells, 1977). The application of this technique in the
evaluation of blood vessels or the heart is also called echocardiography. It plays important role
in diagnosis of congenital heart diseases as well as IUGR.
Current screening methods using Doppler ultrasound indirectly examine placental
insufficiency in IUGR by detecting maternal adaptations to defective trophoblast invasion
process (Madazli et al., 2003), and fetal circulatory adaptations to acute and chronic hypoxia,
which leads to preferential perfusion of vital organs such as the brain, heart, adrenal glands and
21
spleen (Baschat et al., 2000). More specifically, in order to detect growth restriction, Doppler
can be used to examine maternal uterine arteries and the fetal ductus venosus, but has largely
been used in the fetal arterial system including the umbilical artery and MCA. The Doppler
parameters in these vessels are indicators of potential redistribution of blood flows in the setting
of late-onset IUGR. The utilization of Doppler waveforms in each of these vessels in IUGR
detection is discussed as following.
1.1.2.2.1 Uterine artery Doppler
Doppler ultrasonography of the uterine arteries can be used to assess the uteroplacental
circulation. It is used in prediction of the risk of pre-eclampsia and early-onset IUGR as a result
of abnormal placenta formation involving abnormal trophoblast invasion of spiral arteries
(Campbell et al. 1986). In early gestation, high placental vascular impedance gives a notched
uterine artery Doppler waveform and low diastolic flow velocities. Vascular impedance should
decrease in late gestation and the notch should disappear. The persistence of the uterine artery
Doppler notch in the late second and third trimester has been used to identify abnormal uterine
circulation (Berkley et al., 2012). One of the most widely used Doppler parameters is the
pulsatility index (PI), which is calculated as the peak systolic flow minus the end diastolic flow
divided by the mean flow. The value of PI reflects the resistance of blood flow caused by the
microvascular bed distal to the site of measurement. A high uterine artery PI, indicating high
placental flow resistance, has been associated with increased risk for pre-eclampsia and early-
onset IUGR (Spencer et al., 2005). A recent meta-analysis found that abnormal uterine artery
Doppler indices are associated with a three to four-fold increase in the risk of stillbirth (Allen et
al., 2016). It has been suggested that uterine artery Doppler could provide additional information
in predicting adverse perinatal outcome in late-onset IUGR pregnancy (Severi et al., 2002).
However, a systematic review of diagnostic studies has stated the opposite, that uterine artery
22
Doppler only has limited accuracy in predicting IUGR or other adverse outcomes (Chien et al.,
2000). Therefore, more solid evidence is required before uterine artery Doppler can be used as a
stand-alone monitoring tool for late-onset IUGR.
1.1.2.2.2 Ductus venosus Doppler
Velocity waveforms in the ductus venosus are also used to assess fetal well-being. The
ductus venosus originates from the umbilical vein. It allows the highly oxygenated blood from
the umbilical vein into the right atrium and preferentially directs this blood across the foramen
ovale to the left heart, and ultimately the fetal brain (Cruz-Martines and Figueras, 2009). The
ductus venosus Doppler waveform is biphasic with the first peak corresponding to ventricular
systole. The second peak occurs during ventricular diastole, which is followed by a nadir in late
diastole with atrial contraction (Cruz-Martines and Figueras, 2009). In normal fetuses, there
should be continuous forward flow throughout the cardiac cycle. Adaptations in IUGR fetuses
including reduced cerebral vascular resistance and increased pulmonary and peripheral
resistance contribute to a decreased left ventricular afterload and an increased right ventricular
afterload. Persistent right ventricular afterload that is associated with placental insufficiency
would eventually lead to progressive dysfunction of the right ventricle and elevated end-
diastolic pressure in the right ventricle. As a result, the pressure in the right atrium will increase
and impair the forward flow during atrial systole (Cruz-Martines and Figueras, 2009). This will
eventually cause decreased, absent, or reversed flow in the ductus venosus and be reflected in
Doppler sonography.
It has been shown that in IUGR fetuses, increased ductus venosus PI is associated with a
high stillbirth rate with cardiovascular collapse as the main cause of death in utero. Hecher et al.
(1995) showed that five of eight fetuses with absent or reversed ductus venosus flow died on the
23
day of delivery. A higher ratio between systolic and atrial peak velocities in the ductus venosus
was found in IUGR fetuses and systolic to atrial ratio above the 95th percentile was associated
with adverse perinatal outcome in these fetuses (Rizzo et al., 1994). Several other studies also
suggested the relationship between an abnormal Doppler waveform in the ductus venosus and
adverse fetal outcomes such as fetal death, admission to the neonatal intensive care unit, and
low umbilical artery pH (Baschat et al., 2000; Figueras et al., 2003). However, longitudinal
studies have demonstrated that only the advanced stage of fetal compromise is associated with
abnormal ductus venosus waveforms (Hecher et al., 2001; Ferrazzi et al., 2002). Although the
Doppler waveform in the ductus venosus is useful in detecting severe cases of IUGR, it may not
contribute to the early detection of late-onset IUGR. Consequently, other parameters need to be
used in order to detect milder forms of fetal distress.
1.1.2.2.3 Umbilical artery Doppler
Doppler of the umbilical artery (UA) evaluates the vascular resistance in the placenta on
the fetal side. Under normal conditions such as those shown in Figure 5a, low resistance in the
UA allows continuous forward flow throughout the cardiac cycle (Fisk et al., 1988). Decreased,
absent or even reversed end-diastolic flow in the UA, indicating high flow resistance, is
associated with malformation of placental vasculature or dysfunction of the placenta (Berkley et
al., 2012). An example of absent end-diastolic flow in the UA of an IUGR fetus is shown in
Figure 5b. UA Doppler assessment is widely accepted as the clinical standard for identifying
early-onset IUGR (RCOG, 2002). It has been shown that UA Doppler negatively correlates with
levels of glucose and amino acids in the umbilical cord blood (Karsdorp et al., 1994). Therefore,
it is considered to be an effective measurement of placental function. Clinical studies in early-
onset IUGR have demonstrated that fetuses with absent or reversed end-diastolic flow had a
24
relative risk of 4.0 and 10.6 correspondingly for perinatal morbidity and mortality (Cosmi et al.,
2005).
However, UA PI may not be useful in early detection of late-onset IUGR. In common
with the ductus venosus Doppler, it has been suggested that the UA Doppler only becomes
abnormal in advanced stages of placental dysfunction. Rigano et al. (2001) have shown that by
the time the UA Doppler indicates abnormality, umbilical vein flow is already decreased. In an
animal model of fetal distress, diastolic UA flow only became reversed just before fetal death in
six of seven animals (Morrow et al., 1989). Kingdom et al. (1997) have demonstrated that in the
cases of reversed end-diastolic flow in the UA, more than 70% of arteries in placental tertiary
villi were obliterated. Therefore, UA Doppler is not a good parameter to detect early and mild
signs of placental dysfunction.
McCowan et al. (2000), who studied 186 SGA fetuses, have concluded that UA Doppler
is a good indicator of the severity of IUGR, but not independently associated with neonatal
outcome. In this study, they demonstrated that although SGA fetuses with an abnormal UA
Doppler were born more than two weeks earlier and were smaller in all growth parameters than
those with a normal UA Doppler, they had similar Ponderal Index (a measure of body leanness).
When adjusted for the effect of birth weight and gestational age at birth, UA Doppler was not a
predictor of the likelihood of newborn admission to nursery and length of stay in the hospital
(McCowan et al., 2000).
Interestingly, it has been observed that as the gestational age at onset of IUGR increases,
the likelihood of finding abnormal UA Doppler measures decreases. In one study investigating
the utility of different Doppler parameters in the setting of late-onset IUGR, UA Doppler results
were in the normal range despite the development of brain-sparing physiology indicated by
25
other parameters in up to 20% of SGA cases (Oros et al., 2011). As a result, a considerable
proportion of SGA fetuses with normal UA Doppler are actually late-onset mild IUGR cases
and are at risk for adverse perinatal outcome. This idea is supported by Figueras et al. (2009),
who investigated the neurobehavioral performance in SGA fetuses with normal UA Doppler and
AGA fetuses at corrected age of 40 ± 1 weeks. In 102 SGA fetuses and 100 AGA fetuses, they
found the performance score of SGA newborns was significantly lower, which suggests delayed
neurologic maturation despite normal UA Doppler (Figueras et al., 2009). The poor association
of UA Doppler and neurodevelopmental outcome is further supported by Savchev et al. (2013).
In this study, the 2-year neurodevelopmental outcome of 112 full-term SGA newborns with
normal UA waveforms compared with 111 AGA fetuses were evaluated. After adjusting for
potential confounders such as socioeconomic status, gender, gestational age at birth and parental
smoking, developmental outcome was assessed using the Bayley Scales of Infant Toddler
Development (Bayley III) test. All of the Bayley III measures of cognitive, language, motor and
adaptive skill scores were found to be significantly poorer in the SGA group with normal UA
Doppler (Savchev et al., 2013). UA Doppler may therefore be an insensitive parameter for
placental insufficiency resulting in adverse brain development.
26
Figure 5 Example of normal and abnormal umbilical artery Doppler. a) umbilical artery
Doppler in a 38 weeks’ normal fetus with continuous flow throughout a cardiac cycle. b)
umbilical artery Doppler in a 32 weeks’ IUGR fetus with absent end-diastolic flow.
27
1.1.2.2.4 Middle cerebral artery Doppler
In addition to the UA Doppler, the MCA waveform is another important technique for
detecting fetal adaptation to hypoxemia. The right and left MCAs are the major branches of the
Circle of Willis. Since they carry over 80% of cerebral blood flow, and are usually oriented
perpendicular to the maternal anterior abdominal wall, they are amongst the best suited vessels
for assessing the fetal cerebral circulation (Veille et al., 1993). Under normal conditions as
shown in Figure 6a, the cerebral circulation has high resistance with continuous forward flow
throughout the cardiac cycle (Veille et al., 1993). In the presence of fetal hypoxia, circulatory
adaptation results in redistribution of the blood flow to increase perfusion to vital organs
including the brain (Cohn et al., 1974). Increased cerebral blood flow is effected by cerebral
vasodilation, which is mediated by several mechanisms including the action of adenosine
(Pearce, 2009). In human IUGR pregnancies, this is associated with increased diastolic blood
flow and a reduction in PI (Wladimiroff et al., 1986) (Figure 6b).
It has been suggested that in near term SGA fetuses, MCA PI could be a useful predictor
of adverse outcome, independent of UA Doppler findings (Hershkovitz et al., 2000; Severi et
al., 2002). In Hershkovitz et al.’s study (2000), the authors reported that in 47 SGA fetuses, 34
(72%) had normal UA Doppler results, but nine of the 34 had abnormal MCA PI. In the 13
fetuses with abnormal UA PI, seven of them also had abnormal MCA PI. The ratio of head
circumference / abdominal circumference (a measure of asymmetrical growth), was negatively
correlated with MCA PI (P < 0.001) (Hershkovitz et al., 2000). Therefore, an abnormally low
MCA PI is associated with a disproportionately large head as a result of brain-sparing
physiology. Furthermore, in this study brain-sparing was associated with an increased incidence
of cesarean section and neonatal hospitalization. Severi et al. (2002) showed that SGA fetuses
with abnormal MCA PI had increased risk of fetal distress and delivery by emergency cesarean
28
section. However, the association of MCA PI and risk of fetal distress was only significant when
abnormal uterine artery waveform was taken into consideration. Furthermore, a systematic
review challenged that idea that MCA Doppler alone should be used as an independent predictor
of fetal compromise (Morris et al., 2012).
Figure 6 Example of middle cerebral artery Doppler in a normal and an IUGR fetus. a)
Middle cerebral artery Doppler in a 37 weeks’ normal fetus. b) Middle cerebral artery Doppler
in a 36 weeks’ IUGR fetus with elevated diastolic flow, therefore, lower pulsatility index.
29
1.1.2.2.5 Cerebroplacental ratio
Despite the controversy regarding the use of abnormal UA Doppler and MCA Doppler
as individual indicators of compromised fetal conditions, a combination of the two known as the
cerebroplacental ratio (CPR) is emerging as a promising predictor of adverse pregnancy
outcomes (DeVore, 2015). The CPR is calculated by dividing the MCA PI by UA PI; and
therefore represents the interaction of placental status and fetal response. An abnormally low
CPR can be obtained in three circumstances: elevated placental flow resistance marked by
increased UA PI; decreased cerebral flow resistance indicated by reduced MCA PI and finally a
combination of the two. Consequently, CPR could be abnormally low when UA and MCA PI
are both close to being normal (DeVore, 2015). An abnormal CPR would indicate either high
placental resistance, brain-sparing or the combination of the two. Conventional thinking would
assume that only SGA fetuses are at risk of placental dysfunction and fetal hypoxia, but it has
been shown that abnormal CPR could be a useful indicator of fetal hypoxia regardless of EFW
(Morales-Rosello et al., 2014; Prior et al., 2013; Figueras et al., 2015). This is crucial because a
substantial proportion of AGA fetuses are also subject to placental insufficiency and fetal
hypoxia. In an AGA model, Prior et al. (2013) showed that abnormal CPR was a better predictor
of the need for emergency cesarean section than abnormal UA or MCA Doppler individually. In
this study, among the 400 AGA fetuses at term, 36.4% of the fetuses had CPR < 10th centile
(according to gestational age) and had cesarean section due to fetal distress; whereas, only 9.5%
of those had CPR between 10th and 90th centile had cesarean section. No fetuses with a CPR
greater than the 90th percentile required cesarean section (P < 0.001) (Prior et al., 2013). This
finding is aligned with another study by Figueras’s group (2015), which assessed 509 fetuses
with late-onset SGA. In this study, amongst fetuses with CPR < 10th centile, 37.5% had adverse
outcome (neonatal acidosis, admission to neonatal unit, 5 min Apgar < 7, etc.); whereas 19.1%
30
of fetuses with CPR > 10th centile had adverse outcome (P < 0.05) (Figueras et al., 2015).
Similarly, in a large cohort study with more than eight thousand late gestation subjects, Khalil et
al. (2014) also supported the utility of CPR by showing that fetuses with abnormal CPR had a
higher rate of admission to neonatal intensive care unit compared to fetuses with normal CPR (P
< 0.004). These studies support the concept that CPR identifies late gestation fetuses at
increased risk for fetal distress and neonatal complications regardless of EFW.
The Prospective Observational Trial to Optimize Pediatric Health in IUGR (PORTO)
study aimed to evaluate the optimal surveillance of fetuses with EFW less than the 10th centile
(Flood et al., 2014). In this multicenter prospective study, 1,200 SGA pregnancies were
recruited. Within the 146 cases with CPR < 1 (regardless of gestational age), 64% were admitted
to the neonatal intensive care unit with a mean length of stay of 31 days, compared with fetuses
with CPR > 1, 22% of which were admitted to a neonatal unit (P < 0.0001). Fetuses with
abnormal CPR had an eleven-fold increased risk of adverse perinatal outcome (P < 0.0001). The
PORTO group also assessed the sensitivity (detection of true IUGR) and specificity (detection
of true non-IUGR) of different CPR cutoffs. They argued that a categorical cutoff of 1 for CPR
was appropriate and achievable for clinical use. However, when compared with using CPR < 5th
centile for gestational age, CPR less than one regardless of gestational age had lower sensitivity
but higher specificity. The sensitivity of CPR in predicting perinatal outcome was also shown to
be higher than UA PI and MCA PI individually, although both of these individual components
were more specific than CPR (Oros et al., 2011). An increasing number of studies now support
the use of CPR as a predictor of pregnancy outcome in both severe and mild forms of IUGR,
and it should be considered to guide risk assessment of IUGR pregnancies in addition to
conventional UA Doppler and EFW evaluations.
31
Doppler technology has allowed insight into the pathophysiology of IUGR. However,
the dependence on blood flow redistribution in growth restricted fetuses could be a major
limitation of the technique. Another important limitation is that abnormalities of many Doppler
parameters only occur in advanced stages of fetal distress and may not contribute to early
detection of IUGR. In addition, chronic hypoxia may eventually alter metabolism and normalize
blood flow distribution as shown in animal models (Richardson & Bocking, 1998; Poudel et al.,
2015). Therefore, the circulatory redistribution may not be seen in those cases, and this is
supported by many studies that demonstrate a proportion of fetuses with adverse perinatal
outcome did not have prenatal Doppler signs of IUGR (Khalil et al., 2015; Prior et al., 2013).
These limitations highlight the need to develop better clinical measures and tools for early and
accurate detection of late-onset IUGR, and therefore enable timely intervention to avoid adverse
perinatal and long-term outcomes.
1.1.3 MRI in fetal studies
1.1.3.1 Safety
For over 20 years, MRI has played an important role in the diagnosis of fetal
abnormalities by identifying additional pathologies that are difficult to visualize by ultrasound
(Anquez et al., 2007). However, concerns have been raised about the safety of MRI in
pregnancy. Concerns about MRI safety in fetal scans relate to issues such as acoustic noise,
possible temperature increase due to radio frequency wave exposure and potential biological
effects caused by strong magnetic fields (Bouyssi-Kobar et al., 2015). Evidence regarding these
important issues is reviewed below.
Intense, sustained noise has been shown to damage hair cells within the cochlea of fetal
sheep (Gerhardt & Abrams, 2000). However, the relative susceptibility to noise of the human
32
and sheep fetus has not been determined, and the magnitude of exposure used in these animal
studies is above what might be expected as a result of fetal MRI in humans. To address the
effect of noise exposure resulting from routine MRI at 1.5T during pregnancy on human fetal
growth and newborn hearing function, Strizek et al. (2015) conducted a retrospective case-
control study from 2008 to 2012, performing hearing screening on a large cohort of neonates
exposed to MRI in utero and non-exposed neonates. No hearing impairment or deafness was
seen in either group. In a recent study directly investigating the effect of MRI duration and
exposure time of radio frequency on hearing, Bouyssi-Kobar et al. (2015) reported normal
newborn otoacoustic emission test findings and normal hearing at preschool age in 72 healthy
pregnancies that underwent fetal MRI (1.5T) at a mean gestational age of 30.5 weeks.
Furthermore, prenatal exposure to 1.5T MRI during the second and third trimester of pregnancy
is not associated with other adverse outcomes in communication, socialization, motor skills or
hearing at preschool age (Bouyssi-Kobar et al., 2015).
Wang et al. (2016) were interested in studying the effect of exposure to MRI during
pregnancy on metabolism. They focused on a hormone called leptin, which is involved in food
intake and associated with several metabolic diseases (Friedman, 2011). They found that
gestational MRI after 20 weeks’ gestation did not have major effects on leptin DNA methylation
in cord blood and the placenta (Wang et al., 2016). The Radiological Society of North America
has recommended MRI as a first-line examination modality in pregnant women who have
suspected acute appendicitis, and it is used as a second line examination for other acute
abdominal pain in pregnant women (Strizek et al., 2015). MRI is already playing a crucial
clinical role as an adjuvant imaging tool in detecting abnormalities that are not identifiable by
ultrasound, particularly in the field of fetal brain development, and the American College of
Radiology practice guidelines suggest there is no conclusive evidence of deleterious effects of
33
MRI at 1.5T on the developing fetus. There would therefore not appear to be any
contraindication to investigating the role of MRI in the evaluation of IUGR.
1.1.3.2 3D modeling
As discussed earlier, an accurate assessment of fetal weight plays an important role in
the clinical management of pregnancy, especially in cases of fetal macrosomia (large for
gestational age) and IUGR. By contrast to the ultrasonographic method of fetal weight
estimation, which uses an indirect calculation based on estimations of other anatomical
parameters, MRI provides a direct measurement of the whole fetal volume, which then can be
converted to fetal weight (Baker et al., 1994; Zaretskey et al., 2003). Zaretskey et al. (2003)
compared birth weights with MR and ultrasound measures of EFW immediately before delivery
in 80 subjects undergoing cesarean section. The MR acquired fetal volume was converted to
weight, based on the equation described by Baker et al. (1994). The correlation between MR
estimated weight with birth weight was 0.95 with a mean absolute error of 129g. By
comparison, the correlation between birth weight and ultrasound EFW (based on Hadlock’s
equation) was 0.85, and the mean absolute error was 225g. The correlation between MR EFW
with birth weight was significantly higher than that of the conventional ultrasound (P < 0.001).
In order to generate a high-quality MRI 3D model and estimate fetal weight accurately,
there are two main requirements. Firstly, the sequence acquisition time has to be short enough
to avoid artifact from fetal motion; and secondly, there should be good contrast between the
uterine wall, fetus, placenta and amniotic fluid (Anquez et al., 2007; Levine, 2001). Several
sequences are available for fetal screening including echo-planar imaging (EPI), T1 weighted
sequences and T2 weighted sequences (Anquez et al., 2007). Even though EPI initially showed
promise for the estimation of fetal weight (Baker et al., 1994), it is now not commonly used due
34
to its low signal-noise-ratio and susceptibility to artifacts (Prayer et al., 2004). T1 weighted
sequences are also suboptimal for fetal weight estimation because of weak contrast between the
uterine wall, fetus, and amniotic fluid (Prayer et al., 2004). Balanced Steady State Free
Precession (SSFP) is called True FISP (True Fast Imaging with Steady Precession) on Siemens
MRI systems. It is currently the most suitable sequence for 3D segmentation as it has short scan
times and excellent contrast between maternal and fetal boundary with dark fetal skin, grey
uterine wall as well as very bright amniotic fluid (Anquez et al., 2007). Using SSFP, relatively
high resolution can be obtained for precise localization of the edges of fetal organs such as
kidney, lung and stomach. SSFP can also be used to measure fetal brain volume because of the
clear boundary between the bright signal from cerebrospinal fluid and the darker signal from the
brain tissue. Figure 7 shows an example of fetal body (a) and brain (b) segmentation.
Figure 7 Example of fetal body and brain segmentation from SSFP sequence. a) Fetal body
segmentation and volumetry of an MRI 3D-SSFP acquisition of a 38 weeks’ gestation fetus. b)
Fetal brain segmentation and volumetry
35
1.1.3.3 Phase contrast and Metric Optimized Gating
Cine phase contrast MRI is a well-known sequence for measuring vessel blood flow.
During phase contrast sequences two gradients with same magnitude but opposite directions are
applied to the tissue. Stationary tissues undergo no net change in magnetic phase, whereas
moving substances, like blood, will experience a different magnitude of the second gradient due
to its different spatial position (McRobbie, 2006). This provides contrast between moving and
stationary tissues, such as flowing blood and muscle correspondingly. In phase contrast images,
the signal intensity is proportional to the velocity of the tissue, with movement in one direction
coded bright and in the opposite direction coded dark (McRobbie, 2006). For both directions of
flow, the MRI signal has a maximum value corresponding to the maximum velocity referred to
as the VENC (McRobbie, 2006). If the flow velocity exceeds the VENC, the signal will alias,
appearing to be moving the opposite direction. Therefore, in order to accurately quantify the
flow within a vessel, it is crucial to set the VENC correctly, i.e. above the maximum flow
velocity expected to occur in the vessel during the acquisition (McRobbie, 2006).
Cardiac gating is an important step in phase contrast MR because it accounts for flow
variation in different cardiac phases, and therefore allows more accurate quantification of blood
flow. With cardiac gating, a set of phase images of a vessel’s cross-section view are generated at
a number of time points in the cardiac cycle to measure the different flow velocities. When the
phase contrast sequence is prescribed perpendicular to the blood vessel and the cross section
area of a vessel is determined, quantification of flow volume is possible. (Powell et al., 2000).
With the average velocity in the vessel calculated, flow volume rate at any time point in the
cardiac cycle is computed by multiplying the average velocity with lumen cross-sectional area.
This technique has been shown to be very accurate in adult volunteers, with ascending aortic
and pulmonary artery flow measurements concordant within 2% (Lotz et al., 2002). Phase
36
contrast can be two-dimensional or three-dimensional. Three-dimensional (3D) phase contrast
permits observation of vessels from any orientation (McRobbie, 2006). However, due to the
long scan times required, this approach is unsuitable for fetal scans.
Another important function of cardiac gating in phase contrast is to reduce artefacts from
cardiac motion (McRobbie, 2006). Cardiac gated phase contrast has been used extensively in
adult and neonatal cardiovascular scanning, with cardiac information generally achieved by
electrocardiographic (ECG) or pulse signal. However, some modifications need to be made in
fetal scans. In fetal cardiac studies, real-time ECG or pulse signals are not readily available
because of electrical insulation of the fetus and contamination of fetal ECG by the maternal
ECG (Ungureanu et al., 2009). Although Doppler ultrasound and fetal electrocardiography can
measure fetal heart rate, these techniques are not generally available in the MRI environment
(Jansz et al., 2010). Therefore, an alternative method of cardiac gating has to be used to
accurately quantify blood flow in fetal vessels.
1.1.3.3.1 Metric Optimized Gating
Metric Optimized Gating (MOG) is an alternative way to perform cardiac gating which
was developed in 2010 by Jansz et al. It is a technique that acquires temporally oversampled
data and then reconstructs retrospectively using hypothetical cardiac triggering. For cine phase
contrast acquisitions, this is achieved by placing a region of interest on a pulsatile fetal artery
within the field of view. A metric detecting the severity of artefact due to mis-gating (entropy) is
then calculated for the region on the reconstructed images, and this process is repeated using
different hypothetical triggers until the lowest entropy is identified (Jansz et al., 2010). This
technique also allows for heart rate variation. This is achieved by adjusting the length of each
heart beat independently until the image metric is optimized (Roy et al., 2013). The technique
37
has been validated in adult volunteers as well as normal human fetuses (Seed et al., 2012). In the
validation study, five adult volunteers were scanned on a 1.5T scanner. They were exercised
using an MR-compatible bicycle to reach a steady heart rate close to that of normal fetal heart
rates. Flow measurements were made in the common carotid arteries and jugular veins to
resemble the size of fetal great vessels using conventional pulse gating and metric optimized
gating. A high level of agreement was found between the phase contrast flow measurements
made using the two approaches (R = 0.96, P <0.001) (Seed et al., 2012). The same study also
demonstrated the feasibility of the technique in late-gestation human fetuses with a high level of
reproducibility (R = 0.96, P < 0.001), inter-observer (R = 0.99, P < 0.001) and internal
validation (R = 0.9, P = 0.002) (Seed et al., 2012). Using phase contrast with MOG, Prsa et al.
(2014) also established preliminary reference ranges for flows in the major fetal vessels of
normal late gestation human fetuses.
1.1.3.4 MR Oximetry Intrauterine hypoxia is one of the major concerns for pregnancies complicated by late-
onset IUGR. In utero assessment of fetal oxygenation could be beneficial in evaluating placental
function and the presence of fetal distress. However, fetal blood sampling for oximetry carries a
risk of fetal loss, and is rarely performed (Vitiello et al., 1998). There are non-invasive methods
for the determination of blood oxygen saturation including near-infrared spectroscopy. Near-
infrared spectroscopy is an optical method whereby penetrating infrared light (700 – 900nm)
allows for the detection of absorption spectra of oxygenated and deoxygenated hemoglobin
(Boushel et al., 2001). Compared to deoxygenated hemoglobin, oxygenated hemoglobin absorbs
more infrared light and allows more red light to pass through. The light that is not absorbed by
the tissue is measured. Then the ratio of the red light measurement to the infrared light
measurement can be converted to oxygen saturation (Boushel et al., 2001). However, near-
38
infrared spectroscopy is not suitable for fetal studies as the vascular structures of interest are too
deep to be interrogated.
Emerging MRI techniques offer the possibility for non-invasive monitoring of
oxygenation, which could be invaluable for studying the fetal condition in utero. MRI
techniques that can be used for the assessment of oxygenation include blood oxygen level-
dependent MRI and quantitative T2 mapping. Both techniques utilize the different magnetic
properties of oxygenated and deoxygenated hemoglobin: oxyhemoglobin is diamagnetic,
whereas deoxyhemoglobin is paramagnetic (McRobbie, 2006).
1.1.3.4.1 Blood oxygen level-dependent MRI
Blood oxygen level-dependent (BOLD) MRI is a technique that detects changes in tissue
oxygenation by utilizing the changes in concentration of deoxyhemoglobin in the small blood
vessels in the tissue. During hypoxia, the increased concentration of deoxyhemoglobin result in
increased inhomogeneity in the local magnetic field, which yields a decreased BOLD signal
(Levine, 2006). Recent studies have investigated BOLD changes in fetal liver, placenta, and
brain in the setting of hypoxia. Using a sheep model, Sorensen et al. (2011) showed that there
was a reduced BOLD signal (5.2 ± 2.2%) in the fetal liver during hypoxia. This finding was
subsequently reproduced in fetal mice by Cahill et al. (2014) who found a decrease of 44% in
the liver BOLD signal during hypoxia, while the brain BOLD signal only decreased by 12%
(Cahill et al., 2014). These findings were interpreted as being in keeping with the known brain-
sparing mechanism referred to in Section 1.1.1.2, whereby circulatory redistribution results in
increased cerebral blood flow and reduced perfusion of the liver. The concept here is that acute
hypoxia induced with maternal ventilation with a hypoxic gas mixture, results in a reduction in
arterial oxygen saturation and low flow, and therefore an overall decrease in the BOLD signal in
39
the liver. By contrast, the brain BOLD signal remains relatively constant regardless of the
systemic oxygen saturation because of a compensatory increase in cerebral blood flow.
However, variable observations were made in fetal brains by BOLD MRI. Sorensen et al. used
1.5T MRI to study the BOLD effect in fetal lambs. They observed increases in the BOLD signal
in the liver, spleen, and kidney during hyperoxia and a reduction in these organs during hypoxia;
whereas the signal in the fetal brain remained constant under both conditions (Sorensen et al.,
2009). Similar findings were observed in their more recent study in 2013 (Sorensen et al., 2013).
By contrast, Wedegartnar et al. (2006) observed a significant reduction in the BOLD signal in
fetal lamb cerebrum and cerebellum under hypoxia at 3T.
Limitations of the BOLD technique arise from the origins of the signal. The signal is
dependent on not only deoxyhemoglobin concentration, but also fractional blood volume and
imaging parameters such as field strength. These factors may explain the different findings
discussed above. The absolute value of the BOLD signal is not a useful indicator of blood
oxygen saturation, as the BOLD signal is comprised of signal returning from the surrounding
tissue as well as the blood. However, the difference in BOLD before and after maternal
oxygenation could provide insights about placental function in the setting of IUGR (Sorensen et
al., 2013).
1.1.3.4.2 Quantitative T2 mapping
In contrast with BOLD MR, which qualitatively assess organ oxygenation, T2 mapping
allows the quantification of the oxygen saturation of blood. T2 is also known as the spin-spin
relaxation time. It is the relaxation time constant of a tissue derived from the rate of decay of its
MRI signal. T2 mapping consists of the acquisition of a series of images with different T2
preparation times. In each voxel, the individual signal intensity at different preparation times
40
will generate a curve of decay, in which the T2 value can be calculated and displayed for the
voxel (McRobbie, 2006).
During hypoxia, the increased concentration of paramagnetic deoxyhemoglobin will
shift the local magnetic field near the red blood cells, which produces shorter T2 (Wright et al.,
1991). The shift of magnetic field is proportional to the concentration of deoxyhemoglobin; and
the T2 signal is proportional to blood oxygen saturation (Wright et al., 1991). T2 signal intensity
can therefore be used to calculate oxygen saturation if the relationship between them is known.
In 1991, Wright et al. (1991) reported a conversion from T2 to SaO2 (%O2) for adult blood
based on the following equation:
where T2O is the T2 of fully oxygenated blood (about 250ms at 1.5T) and K is a constant
depending on the magnetic field strength, the refocusing interval of the T2 preparation sequence
and hematocrit. This approach has been validated in ten children with congenital heart disease
undergoing invasive cardiac catheterization and MRI at 1.5T (Nield et al., 2005). By performing
T2 mapping in the ascending aorta, superior vena cava, main pulmonary artery and left atrium,
Nield et al. calculated the oxygen saturation in each of the above vessels/chambers based on the
equation defined by Wright et al. (1991). The calculated oxygen saturations were compared with
the measurements made by cardiac catheterization. The investigators found a strong agreement
between the two measurement methods (r = 0.825; P < 0.001) indicating that quantitative T2
oximetry is feasible in young children. The feasibility of this technique in fetal scans is further
supported by a validation study performed in eight sheep fetuses under control and hypoxic
conditions (Wedegartner et al., 2010). In this study, catheter measured oxygen saturation in the
41
carotid artery were well correlated with MR calculated saturation in the left ventricle (r = 0.87)
and right ventricle (r = 0.89) at baseline and during hypoxia, demonstrating the potential of the
technique to detect fetal hypoxia (Wedegartner et al., 2010).
Challenges with the use of this technique include artefacts arising from fetal motion and
partial volume effects. Partial volume effects refer to the loss of contrast between two adjacent
tissues because of an insufficient resolution, when the image voxel is occupied by tissue other
than the one of interest. This could be particularly problematic in fetal scans due to the small
sizes of fetal vessels. For example, the diameter of fetal pulmonary arteries is less than 3 mm at
19 weeks’ gestation and less than 10 mm at 40 weeks’ gestation (Ruano, 2007). In order to
obtain accurate vascular T2 measurements, a high spatial resolution and a slice thickness that is
less than or equal to the vessel diameter is required (Stainsby & Wright, 1998). Due to MR
hardware limitations, some extremely small slice thickness would be too difficult to achieve,
and high resolution is at the cost of longer scan time and lower signal.
In order to minimize artifacts arising from cardiac motion, Giri et al. developed an
automatic non-rigid motion correction technique for myocardial T2 mapping acquired during
free-breathing (Giri et al., 2012). In this approach, corruption of the T2 quantification resulting
from incorporation of signal from tissues surrounding the region of interest due to motion is
corrected mathematically (Giri et al., 2012). The authors demonstrated that T2 variability was
significantly reduced when the motion-correction algorithm was applied (Giri et al., 2012). This
non-rigid registration algorithm is implemented on Siemens systems, and may improve the
fidelity of T2 mapping of blood in fetal vessels. During T2 acquisition, motion correction could
correct for the displacement of the fetus resulting from normal breathing of the mom, as well as
subtle cardiac and body motion of the fetus. With this approach, quantitative T2 measurements
42
of fetal blood could be more feasible for late-gestation fetuses when the vessel sizes are large
enough to minimize partial volume effect. Figure 8 is an example of T2 mapping of several
major fetal vessels.
Figure 8 Example of T2 mapping. a) T2 mapping of fetal main pulmonary artery (MPA)
ascending aorta (AAo) and superior vena cava (SVC); AAo is brighter (has higher T2) than
MPA; SVC is the darkest. b) T2 mapping of umbilical vein (UV) and umbilical artery (UA), UV
is brighter than UA.
A combination of blood flow measurement and oximetry in fetal vessels using MRI
would allow calculation of fetal oxygen delivery and consumption in the fetal body and specific
fetal organs such as the brain (Rurak et al., 1990). In combination with the estimation of fetal
weight using 3D technology, MRI could therefore enable the assessment of the fetal condition
through an approach incorporating fetal hemodynamics, metabolism and growth assessment.
1.2 Neurodevelopment in IUGR and brain MRI
1.2.1 Cerebral oxygenation and neurodevelopment in IUGR
Despite “brain-sparing”, there is evidence to suggest that fetal growth restriction could
have a long-term effect on neurodevelopment. Late gestation is an important period of brain
development. Brain development is thought to be closely coupled to oxygen delivery and
43
oxygen consumption of the brain tissue. As discussed in section 1.1.1.2, oxygen deprivation
could lead to inhibition of protein synthesis. This would potentially affect brain cell growth and
maturation as well as signaling transmission. To date, fetal brain oxygenation has primarily been
studied using invasive procedures in animal models. For example, Rurak et al. (1990)
investigated the cerebral hemodynamic adaptation to acute hypoxia in a sheep model and found
that perfusion of a cerebral hemisphere can increase up to two-fold during hypoxia.
However, chronic hypoxia appears to produce a response that is very different from
those elicited by acute hypoxia (Pearce, 2006). Ultrasound studies in human fetuses suggest that
blood flow redistribution towards the brain also occurs in chronic hypoxia, and this is supported
by increased blood flow velocity in the cerebral arteries in IUGR fetuses. However, Poudel et al.
employed a carunclectomy sheep model to study the distribution of the fetal circulation in the
setting of chronic hypoxia (Poudel et al. 2015). On post mortem examination, the IUGR fetuses
had increased relative brain weight to the body weight typical of human IUGR. However,
interestingly the fetal microsphere measurements of the distribution of the cardiac output
indicated there was no associated increase in cerebral blood flow.
While the cerebral vasodilation seen in acutely hypoxemic fetuses is likely to be
neuroprotective, it may not be adequate in the setting of severe hypoxia, and presumably cannot
be maintained for long periods without injury to other organs. In animal studies, the adenosine
mediated cerebral vasodilation associated with acute hypoxia is dampened during chronic
hypoxia, while neuronal metabolism is downregulated, resulting in a reduced requirement for
oxygen (Pearce, 2006). Accordingly, despite some degree of blood flow redistribution, brain
weight and brain volume in IUGR pregnancies are significantly lower compared to controls in
animal models and in human subjects (Chen et al., 2011; Tolsa et al., 2004). While animal
44
models of chronic fetal hypoxia indicate preservation of neuronal numbers, dendritic
arborization is reduced and white matter myelination is delayed (Tolcos et al., 2011; Rees et al.
2005). Brain size is closely associated with intelligence, and small changes in cortical structure
may affect cortical functioning (Wang et al., 2015). Therefore, it would not be surprising to see
suboptimal neurodevelopment in children born with late-onset IUGR.
A longitudinal follow-up study by Von Beckerath et al. (2013) evaluated the 2-year
neurodevelopmental outcome in 146 IUGR infants and 215 SGA infants who were grouped
based on abnormal Doppler waveforms in the umbilical artery and MCA. By performing tests
on infants’ cognitive, psychomotor and motor skills with examiners blinded to the group
assignment, the authors observed a significantly higher rate of neurodevelopmental impairment
in the IUGR group compared to the constitutionally SGA group (Odds Ratio = 5.5, 95% CI: 2.8
to 11.1). Three IUGR children had cerebral palsy, whereas none were affected in the SGA group
(Odds Ratio = 3.3, 95% CI: 1.8 to 6.4) (Von Beckerath et al., 2013). Cerebral palsy is a
permanent movement disorder that is caused by injury or abnormal development of brain
regions that control movement, balance and posture (Wang et al., 2015). The association of
IUGR and cerebral palsy has also been demonstrated in a population-based case-control study
that investigated more than 350,000 singleton births that were delivered at or after 35 weeks’
gestation (Blair & Nelson., 2015). The odds of cerebral palsy were almost nine-fold higher
(Odds Ratio = 4.16, 95% CI: 2.5 to 6.8) in fetuses with birth weight less than two standard
deviations below the median compared to AGA infants (Blair & Nelson., 2015).
Lohaugen et al. (2013) were interested in studying the effect of IUGR on long-term
neurodevelopment. They examined the association of SGA and cognitive function by comparing
the intelligence quotient (IQ) at age 19 to 20 years in 59 SGA and 81 AGA subjects (Lohaugen
45
et al., 2013). Although the IQ scores were within normal ranges in both groups, the SGA group
had significantly lower IQ than AGAs (P = 0.001). Furthermore, when they divided the SGA
group into IUGR and non-IUGR subgroups based on the growth rate of the fetus, they found
that only the IUGR subgroup had a significantly lower IQ scores than controls (Lohaugen et al.,
2013). This finding is in keeping with Leitner et al., who evaluated the developmental outcomes
of 123 late-onset asymmetrically grown newborns at 9 to 10 years of age. In comparison with
AGA children, the biometry parameters including head circumference, height and weight
remained lower in the IUGR group. Moreover, children born with IUGR had significantly lower
IQ (P < 0.0001) and school achievements (P < 0.001) (Leitner., 2007). IUGR could also be a
risk factor for depression in adulthood. One study reported that young adults aged 18 to 27 years
who were born SGA were four times more likely to use anti-depressant medication and were 2.5
times more likely to report a depression diagnosis (Raikkonen et al., 2008) compared to the
general population. These findings highlight the possible neurodevelopmental implications of
fetal growth restriction and the need for timely intervention that could possibly avert the
neurodevelopmental burden associated with late-onset IUGR.
1.2.2 Brain MRI
Since the ultimate goal of fetal health assessment in late-onset IUGR is to optimize
perinatal brain development, it may be helpful to look into brain oxygenation and development
directly. As discussed earlier, MRI now appears to allow the measurement of both blood flow
and blood oxygen saturation in the fetus. Therefore, this new MRI technology potentially offers
the means to make the first measurements of human fetal cerebral oxygen delivery and
consumption. In addition, MRI is one of the key diagnostic tools for the clinical evaluation of
early brain development and brain injuries. The advantages of MRI for studying the brains of
newborns include the lack of ionizing radiation, and the high-resolution images and tissue
46
contrast offered by a range of sequences (Smyser et al., 2012). Conventional morphologic MRI
neuroimaging is further enhanced by advanced techniques, including diffusion-weighted
imaging (DWI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS),
which provide additional information about brain microstructure and metabolism.
1.2.2.1 DWI
DWI estimates the rate of water diffusion at each image voxel. Water diffusion in a
sample of tissue is highly dependent on its cellular environment; therefore, DWI may provide
information about the changes in tissue microstructure (Le Bihan & Breton, 1986). The apparent
diffusion coefficient (ADC) is a measure of the magnitude of water molecule diffusion. It
decreases as myelination increases in the white matter (Schneider et al., 2007). Postnatal studies
have demonstrated an association between ADC and brain maturation (Mukherjee et al., 2001;
Schneider et al., 2004). ADC in deep white matter areas and basal ganglia both peak at 30
weeks’ gestation and decline afterward (Schneider et al., 2007). This finding might be due to
increased cellularity and myelination in these structures during the last weeks of pregnancy
(Schneider et al., 2007). A high white-matter ADC value at a given gestational age could
therefore be associated with delayed maturation. In addition, it has been shown that DWI is
capable of detecting acute and chronic brain injuries associated with hypoxia in newborns and
fetuses (Boichot et al., 2006; Erdem et al., 2007). For example, a comparison of 12 cases of
SGA and seven normal fetuses showed a 12% increase in ADC in the pyramidal tract, as well as
higher ADC in the frontal lobe, occipital lobe, and corpus callosum (Sanz-Cortes et al., 2010).
Therefore, brain ADC in late-onset IUGR fetuses and newborns may provide important insight
into brain maturation in the setting of growth restriction.
47
Figure 9 Example of newborn brain Diffusion Weighted Imaging. Example of diffusion-
weighted imaging in a normal newborn (corrected gestational age at 41 weeks). Brighter area
indicates more rapid water diffusion. ROIs were drawn in the frontal and posterior white matter
areas bilaterally at the level of the basal ganglia.
1.2.2.2 DTI
By contrast to DWI, which describes the rate of water diffusion in general, DTI can be
used to characterize the spatial distribution of water diffusion in each voxel of an image, and
provide an impression of microstructural development in the brain (Mukherjee et al., 2002). The
diffusion tensor is characterized by diffusion values in three orthogonal directions (McRobbie,
2006). Fractional anisotropy (FA) describes the variance of those values and therefore measures
directionality of water diffusion. FA ranges from zero to one, describing absolute isotropic
diffusion (diffusion in all directions) and anisotropic diffusion (diffusion in one direction),
48
correspondingly (McRobbie, 2006). Brain white and grey matter have similar water content, but
different FAs. This is because water diffusion is less restricted and more directional in white
matter, which consists mainly of axon tracts and myelin sheath. As gestational age increases,
white matter FA increases, indicating increased directionality of water diffusion due to
maturation and myelination of the axons (Berman et al., 2015). On the other hand, FA of the
cortical grey matter has been shown to decrease with maturation (Deipolyi et al. 2005;
McKinstry, 2002). The high FA in the cortical grey matter in early development is thought to be
attributed to the presence of radial glial cells that guide neuronal migration and development of
apical dendrites of immature neurons in the cortical grey matter. As the brain matures, the
decline in the radial component of diffusivity will result in decreased FA. In addition, the
development of complex synapsis between neuronal cell bodies in the cortical grey matter also
contributes to the decrease in the FA (McKinstry, 2002).
The utility of DTI in the investigation of brain maturation has been applied to different
populations, including preterm newborns, newborns with congenital heart disease and IUGR
fetuses. For example, in a rabbit IUGR model, Eixarch et al. found decreased white matter FA in
growth-restricted pups (Eixarch et al, 2012). This study also revealed that FA correlated with
neurobehavioral outcomes in multiple brain region. This finding is similar to those observed in a
human model by Batalle et al. (Batalle et al. 2012). In this study DTI demonstrated significantly
lower white matter FA in IUGR infants (P = 0.02). In addition, the authors reported that the
structural brain network features at one year of age could predict neurodevelopment at two-
years of age. Impaired postnatal growth was also shown to be associated with delayed
microstructural development of the cerebral cortex reflected in higher FA in the preterm infants
(Vinall et al., 2013). Through these studies, we now understand that the brain undergoes a
predictable pattern of development in the cerebral cortex and white matter, and DTI could be a
49
useful tool to assess brain maturation in terms of its microstructure.
Figure 10 Example of newborn brain Diffusion Tensor Imaging. Example of color coded
fractional anisotropy map in a normal newborn (corrected gestational age at 41 weeks). Brighter
area indicates more directionality of water diffusion. Water diffusion in the right-left plane is
colored red, superior-inferior in blue and anterior-posterior in green.
1.2.2.3 MRS
Another advanced MRI technique, MRS, also provides a valuable tool for investigating
neonatal brain development in vivo. MRS is used to determine the relative level of molecules by
comparing their MRS spectra (McRobbie, 2006). Several brain metabolites that are commonly
studied by MRS are N-acetylaspartate (NAA), choline, creatine, and lactate. NAA is a neuronal
marker localized in oligodendrocytes. Its presence in normal conditions indicates neuronal
integrity, which is found to be increased with advancing maturity (Bhakoo & Pearce, 2000;
Kreis et al., 2002). Choline is associated with cell membrane turnover, and creatine is a marker
of brain energy metabolism (Story et al., 2011). Changes in these metabolite ratios could be
50
indicators of brain development and a predictor of neurodevelopmental outcome (Miller et al.,
2002). Story et al. (2011) performed MRS under 1.5T on a cohort of IUGR and normal fetuses
in the second and third trimesters. They reported reduced NAA:choline and NAA: creatine
ratios in IUGR fetuses. The lower NAA:choline ratio in SGA and IUGR fetuses was also
observed by another group of researchers who performed MRS under 3T (Sanz-Cortes et al.,
2015). They showed that the NAA:choline ratio was significantly correlated with biparietal
diameter (r = 0.27, P = 0.021), head circumference r = 0.26, P = 0.026) and corpus callosum
length and area (Sanz-Cortes et al., 2015). However, Simoes et al. (2015) observed contradicting
results when they scanned 40 SGA and 30 AGA infants under 3T. They reported a significantly
increased NAA:creatine ratio and a non-significant increase in the NAA:choline ratio in SGA
fetuses, and the NAA:creatine ratio at one year of age was shown to be negatively correlated
with cognitive scores according to Bayley’s test (Simoes et al., 2015). Therefore, more evidence
is needed to establish the association between growth restriction and MRS measured brain
metabolite ratios.
Lactate is another commonly studied brain metabolite. A lactate peak on MRS indicates
glycolysis associated with oxygen deficiency. Under normal conditions, the level of lactate
should be undetectable by MRS. Different studies in IUGR pregnancies have shown that
hypoxia in utero is associated with increased lactate in the fetal brain (Story et al., 2011; Cetin
et al., 2011; Azpurua et al., 2008). However, an elevated level of lactate is not necessarily
associated with brain injury (Kreis et al., 2002). Story’s study (2011) found that lactate peaks in
five of the 28 IUGR fetuses and in three of the 41 normal fetuses; three of the five IUGR fetuses
with lactate had a good short-term outcome. Therefore, it is hypothesized that lactate may play a
role in normal cerebral development and could act as a fuel source in immature brains
(Tabernero et al., 1996).
51
Cerebral maturation can also be studied by other MR techniques. These include
evaluation of cortical folding, where cortical sulcation should be more complex as the brain
matures (Egana-Ugrinovic et al., 2013), as well as diffuse excessive high signal intensity
(DEHSI) on T2-weighted images. DEHSI corresponds to high water content in the brain region
and is also thought to be an indicator of brain immaturity, shown by preterm infant studies
(Kidokoro et al., 2011). All of these MRI techniques enable the evaluation of not only the gross
structural brain growth, but also the functional and microstructural development of the brain.
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2 Rationale and Research Objectives Unlike early-onset IUGR, in which delivery is usually delayed until imminent fetal
demise because of the severe complications associated with significant prematurity, the
postnatal complications associated with late preterm delivery in the setting of late-onset IUGR
are much less significant, and there remains interest in the concept that neurologic injury might
be avoided through modification of the timing of delivery. However, the potential benefits of
early delivery need to be weighed carefully against the morbidity associated with unnecessary
iatrogenic late-preterm delivery. Furthermore, optimizing the timing of delivery depends on
accurate diagnosis and monitoring of the condition. While early-onset IUGR can be diagnosed
reliably by UA PI, the accurate identification of late-onset IUGR in utero may pose a challenge.
Fetal weight estimation by ultrasound, which is often used to diagnose IUGR, is subject to a
mean error of 7–10% with a tendency to overestimate low fetal weight and underestimate high
fetal weight. This high error rate is mainly because the EFW is calculated based on indirect
biometric parameters, and late-onset IUGR fetuses are not necessarily small (Oliver, 2013;
Baker et al.,1994). As we have seen, UA PI is also known to perform poorly in late gestation
with high false-positive rates (Boers et al., 2010). CPR has been shown to be a more sensitive
indicator of late-onset IUGR than UA PI and EFW. However, in the setting of chronic fetal
hypoxia, where circulatory adaptation gives way to metabolic change, even CPR may be flawed.
Therefore, the Doppler changes resulting in a low CPR in the setting of late-onset IUGR may
pseudo-normalize, and some affected cases may be missed. It is possible that limitations in our
ability to diagnose IUGR account for the negative results of studies like DIGITAT that have
attempted to demonstrate differences in IUGR outcomes with modifications in the timing of
delivery.
53
Fetal MRI could provide additional information about the hemodynamic consequences
of intrauterine growth restriction and accurately measure fetal weight and brain size (Baker et
al., 1994). While Doppler ultrasound is primarily used to imply redistribution of the fetal
circulation based on the pulsatility of vessels supplying different vascular beds, phase contrast
MRI can measure the absolute flow in blood vessels, and therefore directly measure circulatory
redistribution (Lotz et al., 2002). Conventional phase contrast MRI requires cardiac triggering,
which allows for adequate temporal and spatial resolution to accurately measure the blood flow
in a vessel. Cardiac triggering, or “gating” is conventionally achieved by timing MRI
acquisitions to the QRS complex of the ECG. However, the fetal ECG is not readily available
for MRI because of interference from maternal electrophysiologic signals. MOG offers an
alternative to ECG gating and makes the quantification of blood flow using high resolution cine
phase contrast MRI possible in the human fetal circulation (Jansz et al., 2010). Finally, by
exploiting the different magnetic properties of oxygenated and deoxygenated hemoglobin,
oximetry of fetal blood in vivo using MRI has become feasible and may offer a safe alternative
to invasive cordocentesis (Sun et al., 2015). Invasive studies in animal models and humans
using cordocentesis have demonstrated profound reductions in fetal blood oxygen saturation
(SaO2) in IUGR fetuses despite normal blood flow distribution (Poudel et al., 2015). Fetal
monitoring might, therefore, be improved by the direct assessment of fetal oxygenation (i.e.
fetal oximetry).
Although human fetal hemodynamics and oxygenation in the setting of both early and
late-onset IUGR are of interest, the MRI technique we have developed is currently unsuitable
for use in early-onset IUGR fetuses because it is limited by the requirement for adequate signal
and spatial resolution while achieving practical scan times. However, the sizes of the major fetal
vessels in late gestation fetuses allows reasonable image quality and for the imaging to conform
54
to established criteria for accuracy. Therefore, we were interested to explore the assessment of
placental function using a combination of phase contrast MRI and MR oximetry in late
gestation. The combination of umbilical vein flow and oxygen content allows the calculation of
fetal DO2, which could be a useful indicator of placental function. Fetal VO2 can also be
calculated with the addition an umbilical artery oxygen content measurement, and this gives a
measure of fetal metabolism. Together with direct measurement of blood flow to the brain, DO2
and VO2 allow us to accurately determine the fetal circulatory and metabolic adaptations to
hypoxia, which is commonly associated with IUGR (Rudolph, 2009; Acharya & Sitras, 2009).
Similarly, an approximation of cerebral oxygen delivery (CDO2) and cerebral oxygen
consumption (CVO2) can also be calculated using this approach. The evaluation of fetal brain
perfusion and oxygenation will provide direct information about cerebral vascular and metabolic
adaptations to hypoxia, and their impact on brain growth and development. Since the ultimate
goal of fetal health assessment in late-onset IUGR is to optimize perinatal brain development, a
direct approach to assessing brain oxygenation may confer considerable benefits in facilitating
more judicious timing of delivery (Von Beckerath et al., 2013; Baschat, 2011).
Postnatal brain MRI may also be used to explore the neurodevelopmental impact of
IUGR. Recent reports suggest that growth restriction occurring closer to term is associated with
impaired brain maturation and neurodevelopment (Baschat, 2011; Cruz-Martinez & Figueras,
2009). Advanced MRI techniques, such as DTI and MRS are established tools for studying
neonatal brain development in vivo. DTI can assess the 3D spatial distribution of water diffusion
in brain tissue, while MRS can measure metabolic changes associated with brain development
(Kreis et al., 2002; Mukherjee et al., 2002). Together, they provide measures of brain
biochemistry and microstructural development. However, recent studies of late-onset IUGR
55
brain metabolism by MRS have shown controversial results and the real impact of late-onset
IUGR remains unknown (Story et al., 2011; Sanz-Cortes et al., 2015; Simoes et al., 2015).
We were therefore interested in using MRI to investigate the relationship between
hemodynamic parameters and brain growth and neurodevelopmental outcome in IUGR fetuses
and investigate the feasibility and utility of this technology for identifying late-onset IUGR in
utero. The objectives of this research were as follows:
Objective 1: to characterize fetal cardiovascular physiologic adaptations to late-onset IUGR by
comparing the hemodynamics of IUGR and normal fetuses.
Objective 2: to assess the performance of MRI parameters for the detection of late-onset IUGR,
comparing them with conventional ultrasound measures.
Objective 3: to investigate the effect of IUGR on neurodevelopment, specifically the
relationship between cerebral oxygen delivery in utero.
Through these objectives we aimed to test the following hypotheses:
Hypothesis 1: Human late-onset IUGR is associated with redistribution of the fetal circulation,
arterial desaturation and reduced oxygen delivery and consumption
Hypothesis 2: MRI will out-perform conventional Doppler ultrasound in the identification of
late-onset IUGR through the ability to identify arterial desaturation
Hypothesis 3: Despite brain sparing physiology, IUGR is associated with reduced fetal cerebral
oxygen delivery, the extent of which will associate with evidence of brain dysmaturation in the
infant
56
3 Methods We conducted a prospective cross-sectional case control study comparing biometric and
hemodynamic measurements in fetuses with and without late-onset IUGR and subsequently
compared their neuroimaging findings and developmental outcomes. The study was carried out
in two phases. In phase one we investigated objectives 1 and 2 to study the human fetal
adaptation to late-onset IUGR by MRI as well as the performance of MRI compared to
ultrasound. In phase two we looked at objective 3, in which we compared the brain development
between normal and late-onset IUGR newborns.
This study was approved by the research ethics boards at the Hospital for Sick Children
(REB1000028082) and the Mount Sinai Hospital (REB 11-0229-E). We performed research
MRI and ultrasound examinations on a group of normal and suspected late-onset IUGR fetuses
in the final weeks of pregnancy. We attempted to validate our methodology by analyzing inter-
and intra- observer variation and reproducibility (Appendix I and II). Placental histology,
anthropometric measurements, and a brain MRI were performed soon after birth. A composite
scoring system, based on both pre- and postnatal parameters, was used to define IUGR. The
performance of MRI and ultrasound parameters were compared in terms of their concordance
with postnatal evidence of IUGR. Brain MRI findings and preliminary developmental
assessment scores were compared between the two groups.
3.1 Participants Pregnant women between 32 and 41 weeks of gestation with singleton pregnancies were
invited to participate in the study through the Obstetric Outpatient Clinic at Mount Sinai
Hospital in Toronto, from May 2013 to February 2015. Our recruitment included pregnant
women with fetuses across a range of weight percentiles. However, in order to provide a study
57
group enriched for IUGR cases, recruitment was focused on SGA fetuses. Written consent was
obtained from every subject. Gestational age was determined from first trimester crown-rump
length measurements. Pregnancies complicated by chronic maternal illnesses, including
diabetes, autoimmune disease, and hypertension, were excluded. Fetuses with anemia,
prenatally diagnosed congenital malformations, or genetic syndromes were also excluded. The
results of the MRI scan and research echocardiograms were not generally used to guide clinical
management. However, when MRI found previously undetected abnormalities that might be
significant for the management of pregnancy, the subject and obstetrician caring for the subject
were informed. In one of our subjects, the MRI scan detected four nuchal cords that were
previously undetected. Therefore, her delivery plan was changed from an induction to a
caesarean section.
3.2 Fetal hemodynamic assessment
3.2.1 MRI protocol in fetal study
In phase one, which is the fetal study, each participant completed an MRI safety
screening questionnaire before the MRI scan. During MRI scans, subjects were instructed to
remain as still as possible. We asked the subjects to avoid eating for two hours before the scan
in order to minimize fetal motion. Subjects were invited to lie on the MRI table in a lateral or
supine decubitus position according to their preference, and they were able to change position
during the scan if necessary. A body-matrix coil was placed on the maternal abdomen, as close
to the fetal thorax as possible to provide a better signal. A second coil was placed over the
subject’s back when she chose to lie in lateral decubitus position so that the signal would be
improved across the whole field-of-view. Scans were performed on a clinical 1.5 Tesla MRI
58
system (Siemens Avanto, Erlangen, Germany) by a clinical radiologist (MS) or an MR
technologist (NG). Table 1 shows the fetal MRI sequence protocol. The sequence parameters
were based on commercially available cardiac MRI sequences. Velocity encoding sensitivity
was tailored according to vessel types: 150 cm/s for arteries, 100 cm/s for veins and 50 cm/s for
umbilical vein. T2 mapping used five T2 preparation times, tailored to span the expected T2 of a
given vessel (0ms, 0.33*T2, 0.66*T2, 1.00*T2 and 1.33*T2), with 4 seconds of magnetization
recovery between successive T2 preparations.
Table 1. MRI sequence protocol. Velocity encoding sensitivity tailored according to vessel:
150 cm/s for arteries, 100 cm/s for veins and 50 cm/s for umbilical vein; T2 mapping used 5 T2
preparation times, tailored to span the expected T2 of a given vessel (0 ms, 0.33*T2, 0.66*T2,
1.00*T2 and 1.33*T2). TE, echo time; TR, repetition time; FOV, field of view.
Sequence Type Gating Resp. comp. TE
(ms)
TR
(ms)
Slice thick
(mm) Matrix size
FOV
(mm)
Temp.
resol. (ms)
Scan time
(s)
3D-SSFP 3D – Breath- hold 1.74 3.99 2 256×205×80 400 – 13
Phase contrast 2D MOG – 3.15 6.78 3 240 × 240 240 54 36
T2 mapping 2D PG – 1.15 3.97 6 224 × 181 350 4000 16
3.2.1.1 Fetal body weight and brain weight estimation
A 3D SSFP acquisition allowed the quantification of fetal body weight and brain weight,
according to our previously published technique (Sun et al., 2015). The image was acquired
during a single maternal breath-hold to reduce motion artefact. The average scan time was 13
seconds. Post-processing of the acquisition was performed on a local computer using
commercially available software (Mimics, Materialise Group, Leuven, Belgium). The interface
between the high-signal amniotic fluid and lower-signal uterus and fetus was defined using a
59
combination of threshold, cutting and filling tools. The segmentation software then calculated a
3D model of the fetus to estimate fetal volume. Fetal volume was converted to fetal weight
using a conversion formula: fetal weight (g) = 120g + fetal volume (ml) ×1.03 (Baker et al.,
1994). Then the GA-corrected Z-score of the fetal weight was calculated according to
population-based reference ranges (Kramer et al., 2001). Similarly, by utilizing the contrast
between bright cerebrospinal fluid and darker brain tissue, the fetal brain volume was estimated
by the segmentation software. The fetal brain volume was converted to weight as: brain weight
(g) = brain volume (ml) × 1.04 (Roelfsema et al., 2004). The brain weights were also converted
to GA appropriate Z-scores based on autopsy reference ranges (Guihard-Costa et al., 1995).
3.2.1.2 Blood flow quantification
Prior to the MRI scan, the fetal heart rate was measured for five minutes using a
cardiotocography device (GE Corometric, Fairfield, Connecticut, USA). An appropriate heart
rate was then programmed into the MRI system computer and to ensure oversampling of even
the lowest true fetal heart rate for later reconstruction using MOG. Following localization of the
fetus, SSFP acquisitions were performed in axial, coronal, and sagittal planes to the fetal thorax.
These images were used as the maps to prescribe phase contrast sequences to the major fetal
vessels. We prescribed acquisitions aligned perpendicular to the long axis of the descending
aorta (DAo), superior vena cava (SVC), ascending aorta (AAo), main pulmonary artery (MPA),
ductus arteriosus (DA), umbilical vein (UV), and right and left pulmonary arteries (RPA, LPA)
based on two orthogonal views. The flow in the UV was measured in the mid-intrahepatic
section and away from the umbilical insertion but proximal to portal vein branches to avoid
complex flow behavior. A typical scan time for each vessel was 36 seconds. The raw data were
transferred to a local computer to perform MOG by using MATLAB (Mathworks, USA). The
60
software produced a map and identified the combination of heart rates with the lowest metric
values when a region of interest was placed on a pulsatile artery in the image. The MOG-
corrected data was sent back to the scanner to patch the corrected R to R interval to the raw data
and reconstructed to become more accurately gated images. The reconstructed images that were
incorporated with information about different cardiac phases became “pulsatile”. The flows
were measured with a standard commercial cardiovascular software package (Q-flow 5.6, Medis
Medical Imaging Systems, Leiden, Netherlands). Regions of interest were drawn around each
major fetal vessel listed above on the phase contrast images to estimate the blood flow. The flow
measurements were then indexed to the EFW. Validation analysis of the flow measurements by
phase contrast with MOG technique is shown in Appendix 1.
3.2.1.3 Magnetic resonance oximetry
T2-based MR oximetry has been shown to be feasible in lamb fetuses and human models
(Wedegartner et al., 2010; Sun et al., 2015). In this study, we used the T2 mapping technique
adapted from a sequence designed for myocardial T2 mapping (Giri et al., 2009). It employs a
T2 preparation pulse followed by a rapid SSFP readout with TE 1.15ms and TR 3.97ms. We
used a slice thickness of 6mm, matrix size 224× 181, and field of view of 300mm. This resulted
in an in-plane spatial resolution of 1.3mm. An interval of four seconds between individual T2
preparation was used to ensure adequate magnetization recovery. A typical scan time for each
major fetal vessel was 16 seconds. The diameter of DAo, MPA, AAo, and UV are all over 7mm
at term (Schneider et al., 2005), which ensured a minimum of six pixels across the vessel. The
SVC in a term baby has a diameter of about 5mm, and therefore the vessel may cover at least
four pixels. Fetal motion is a challenge for T2 mapping techniques because of the small size of
the fetal vessels. Therefore, a non-rigid motion correction algorithm (Myomaps, Siemens
Healthcare, Erlangen, Germany) that has been incorporated into the T2 mapping sequence
61
enabled correction for small fetal and maternal movements that occurred during each T2
preparation image. The sequence was repeated when there were more gross fetal movements.
The spatial resolution and motion correction are crucial to avoid “partial-volume effect”, which
describes an artefact when surrounding tissue signal contaminates the region of measurement
(Stainsby & Wright, 1998). T2 relaxation time was measured from the T2 maps with a region of
interest placed over only the central 50% of the vessel in accordance with established criteria
(Stainsby & Wright, 1998). Then we used a previously reported conversion from T2 to oxygen
saturation (SaO2) to estimate the SaO2 in the fetal blood vessels (Wright et al., 1991).
3.2.1.4 Combined ventricular output (CVO), DO2 and VO2 calculation
CVO was estimated from the sum of AAo and MPA flows plus an estimated coronary
blood flow of 3% of CVO based on lamb studies (Rudolph, 2009). Pulmonary blood flow (PBF)
was calculated as the sum of RPA and LPA flows (RPA and LPA). Fetal DO2 was calculated as
the product of UV flow and UV oxygen content (Sun et al., 2015). Oxygen content was
calculated as Cuv = [Hb]× UV SaO2 × 1.36 (1.36 is the amount of oxygen bound per gram of
hemoglobin). Currently, no available method can measure fetal hemoglobin concentration non-
invasively. Therefore, a gestational age-appropriate population average (0.15g/ml) (Nicolaides
et al., 1988) was used in the calculation of DO2: DO2 = UV flow × 0.15 × UV SaO2 × 1.36.
To calculate fetal VO2, the difference in oxygen content of UV and UA was needed. Due to the
small size of the UA, the T2 cannot be directly measured in this vessel. However, the T2 of the
DAo measured at the level of fetal diaphragm was used to estimate the SaO2 in the UA, because
the DAo directly supplies the UA blood. VO2 was calculated as: VO2 = UV flow × 0.15 × (UV
SaO2 - DAo SaO2) × 1.36. Fetal oxygen extraction fraction (OEF) was calculated as
VO2/DO2. Finally, because the size of vessels that exclusively supply and drain the brain are
62
small, SVC flow was used in CVO2 and CDO2 calculations because cerebral blood flow
accounts for the majority of the venous drainage to the SVC in the fetus (Sun et al., 2015).
Therefore, cerebral oxygenation was calculated as: unindexed CDO2 = unindexed SVC flow ×
0.15 × AAoSaO2 × 1.36 and unindexed CVO2 = unindexed SVC flow × 0.15 × (AAo SaO2 –
SVC SaO2) × 1.36. CDO2 and CVO2 were also indexed to the estimated brain weight.
3.2.2 Doppler (UA and MCA)
A research ultrasound was performed on the same day as the MRI in every subject. This
included Doppler measurements of MCA and UA PI, and CPR was calculated as MCA PI/UA
PI. An EFW was also obtained from the ultrasound, based on biparietal diameter, head
circumference (HC), abdominal circumference, and femur length. In addition to the research
ultrasound, all clinical Doppler measurements performed at Mount Sinai Hospital after 30
weeks’ gestation were collected.
3.2.3 IUGR diagnosis
Due to the absence of an accepted gold standard for IUGR diagnosis, we developed an
IUGR scoring system that accounts for both pre- and postnatal evidence of fetal growth
restriction. In our IUGR scoring system, one point was allocated for a positive result in each of
the four categories, and a score of ≥ 2 defined IUGR:
1) birth weight ≤ 3rd percentile or ≥ 20% drop in percentile of ultrasound-based EFW over serial
visits ≥ 2 weeks apart;
2) Ponderal index < 2.2 (g/cm3);
3) lowest CPR after 30 weeks < 5th percentile; or abnormal UA flow pattern (absence of end
diastolic flow; reversed end diastolic flow);
4) placental histology meets pre-defined criteria for placental under-perfusion (i.e., placental
63
weight <10th, multi-focal infarction, decidual vasculopathy) (Redline, 2008).
Birth weight percentile was calculated for each newborn (Kramer et al., 2001; Davies,
1980). For each subject with birth weight above 3rd percentile, the growth chart was also
collected to identify the presence of reduced growth rate during late pregnancy. The Ponderal
Index measures the leanness of a subject. IUGR fetuses tend to have less subcutaneous fat
compared to normal fetuses, therefore a low Ponderal Index could be an indicator of the
condition. We collected birth weight and length and calculated Ponderal Index: Ponderal Index
= 1000 × mass / height3. A cutoff of less than 2.2 was used as a positive criterion for IUGR,
according to Soundarya et al. (Soundarya et al., 2011). We combined all of the Doppler
(research and clinical) results after 30 weeks of gestation for each subject. We looked up the
percentile of each available CPR using recently published reference ranges (Morales-Rosello et
al., 2015). We recorded the Doppler result when the worst CPR (lowest GA-appropriate
percentile of CPR) was obtained. Subjects with an absence of end diastolic flow or reversed end
diastolic flow were also marked as abnormal for Doppler. Gross and histopathologic
examination of every placenta was performed by an expert in perinatal pathology (SK). The
categorization of the placenta abnormalities was based on the consensus opinion of the perinatal
pathologist (SK) and an IUGR specialist (JK), with reference to criteria established by Redline
et al (Redline, 2008). All of the analyses in the first part of the study utilized this scoring system
for IUGR categorization, except for the receiver operating characteristic (ROC) analysis of the
relative performance of MRI and Doppler for IUGR diagnosis. In the ROC analysis, only post-
natal parameters (meeting over two of categories 1, 2 and 4 listed above) were used to define
IUGR to avoid bias towards CPR.
64
3.3 Neurodevelopment in late-onset IUGR
3.3.1 Newborn Brain MRI The second part of the study included the newborn brain MRI. Infants were scanned using a
“feed and sleep” approach without pharmacological sedation. All infants were screened for MRI
safety. In order to minimize motion artefact, the head was immobilized by a pillow filled with
polystyrene balls and molded into shape by vacuuming. An MR-compatible ECG recorder was
put on the infant’s chest to be used for cardiac gating. Following localizers, 3D SSFP
acquisition was performed for brain volume quantification. Multi-voxel proton MR
spectroscopy was performed in a sample of basal ganglia (grey matter) and centrum semiovale
(white matter) and used to compare the levels of brain metabolites such as NAA, choline,
creatine, and lactate in IUGR and control newborns. ADC is a measure of the diffusion rate of
water molecules in specific tissue, and was measured with Axial DWI. DTI characterizes the 3D
spatial distribution of water diffusion in each voxel of the acquisition. Both DWI and DTI were
performed to evaluate brain microstructure. A typical scan time was 45 minutes to one hour.
Post-processing of the 3D acquisition was similar to the approach described above for fetal
segmentation. The interface between the high-signal cerebrospinal fluid and low-signal brain
tissue was defined using Mimics. ADC was measured in inferior frontal, superior frontal, and
parietal white matter in both hemispheres. FA was measured using a Neuro3D application
embedded in the MRI scanner system. Measurements were made in 13 regions of interest, which
included different regions of white matter and basal ganglia. Table 2 summarizes the newborn
brain MRI protocol. In this part of the study, IUGR was identified based on criterion 1 and 3
listed in Section 3.2.3 (1) birth weight ≤ 3rd percentile or ≥ 20% drop in percentile of ultrasound-
based EFW over serial visits ≥ 2 weeks apart; 2) lowest CPR after 30 weeks < 5th percentile; or
abnormal UA flow pattern (absence of end diastolic flow; reversed end diastolic flow), due to
65
missing postnatal data or placental reports in majority of the patients.
Table 2. Newborn brain MRI protocol. DWI, diffusion weighted imaging; MRS, proton
magnetic resonance spectroscopy; TE, echo time; TR, repetition time; DTI, diffusion tensor
imaging. FOV, field of view.
Sequence Type TE (ms)
TR (ms)
Slice thick (mm) Matrix size FOV
(mm) Scan time
(s)
Axial T1WI 2D 12 1500 4 256×205 140 99
Axial T2WI 2D 205 8620 4 320×256 140 96
MRS multi voxel 144 1500 - 17×19×12 240 186
Axial DWI 2D 102 5200 4 128×128 240 152
3D volumetry
3D 9.2 36 1 256×205×80 400 15
DTI 2D 97 7300 2 - 160 500
3.3.2 Developmental assessment
Developmental follow-ups were undertaken by a neonatologist and developmental
pediatrician (EK) at Mount Sinai Hospital. At four months, eight months, 12 months, and 18
months, the infants’ development in motor, language, social, and cognitive skills were evaluated
using different tests. Posture and Fine Motor Assessment of Infants (Case-Smith & Bigsby,
2000) evaluates hand-eye coordination and the skills using the small muscles in the hands and
fingers in infants aged two to 12 months old. As the infants grow, different fine motor behavior
is expected to be observed. For example, at four months, most infants can bring their hands
together and bring their hands to their mouths; at eight months, they should be able to hold and
shake a toy and move objects from hand to hand; and at 12 months, most infants can drink from
a cup, etc. The Alberta Infant Motor Scale is a measure of motor abilities in infants aged zero to
18 months. The reference ranks were developed from 1990 to 1992 based on 2,200 infants. The
test was used to evaluate infants’ gross motor skills, which are movements using larger body
66
muscles including sitting, standing, keeping balance and changing position, etc. (Piper &
Darrah, 1994). These motor tests were performed at four months of age. At eight months and 12
months, in addition to motor assessments, infants’ social communication and expressive
language skills were evaluated by the Communication and Symbolic Behavior Scales
Developmental Profile (Wetherby, 2002). The profile is based on both parent report and face-to-
face evaluation of a child to assess adaptive behavior, such as connecting and responding to the
feelings of others. At 18 months, the Bayley Scale of Infant Development (Bayley, 2005) was
used to assess infants’ development in areas including cognitive, receptive, and expressive
communication, as well as fine motor and gross motor skills. In the Bayley’s test, the raw scores
of successfully completed play tasks were converted to scaled scores and to composite scores.
Test scores and ranks of the performance of the child in each skill category in the Bayley’s test
were collected and comparisons were made between IUGR and normal subjects.
3.4 Statistical methods All measurements passed the D’Agostino & Pearson omnibus normality test
(D’Agostino et al., 1990) except: UA and PBF in the normal group and MPA T2 in the IUGR
group. The initial analysis compared MRI and ultrasound parameters between IUGR and non-
IUGR fetuses using a Student t-test for normally distributed measurements or a Mann Whitney
test for measurements that were not normally distributed. We then used Pearson’s correlation to
investigate the relationships between measurements. Linear regression and Bland-Altman plots
were used to assess intra- and inter- observer variability and reproducibility for MRI flow and
T2 measurements. ROC curves were created to evaluate the performance of MRI and Doppler
measurements in identifying IUGR. Finally, Fisher’s exact test was used to compare the
67
incidences of lactate peaks in IUGR and normal newborn brains. Statistical analysis was
performed using GraphPad Prism 6.0e, USA. The box and whisker plot uses medians and
quartiles. All values in the text are expressed as means ± standard deviations. P values of < 0.05
were considered statistically significant. “*” indicates significantly different result in the figures.
68
4 Results
4.1 Participants In total, 109 pregnant women were enrolled in our study. 60/109 subjects participated in
newborn brain MRI scan, and 47/109 subjects participated in the infant follow-ups (Figure 11).
69/109 subjects had complete MRI data. 28 of the 69 subjects were excluded because the data
obtained did not include all of the parameters required for categorization into IUGR or normal.
One subject was excluded due to an incomplete study resulting from excessive fetal motion with
limited study time available to complete the study. The remaining 40 subjects were included in
the hemodynamic analysis, and all neonates were born in good condition with the exception of
one stillbirth of an IUGR fetus in the setting of preeclampsia (S06). Based on our IUGR scoring
system, the 40 subjects were categorized into 14 IUGR and 26 normal subjects. Detailed
delivery conditions of the 14 IUGR subjects are shown in Table 3.
Within the normal group, 15 subjects were born by spontaneous vaginal delivery (SVD),
four had induction of labor prior to SVD, three had assisted SVD, two had scheduled caesarean
sections and two had emergency caesarean sections. All of the normal babies were born alive
and well, and none was admitted to the NICU or had any neonatal medical problems. In the
IUGR group, subject S06 chose to deliver the baby by SVD having been counselled that this
mode of delivery was likely to be associated with a significant risk of stillbirth. All other
subjects were born alive and well. S13 and S14 had birth weights above the 3rd percentile.
However, the EFW of subject S13 at 34 weeks was in the 45th percentile, and dropped to the 7th
percentile at 39 weeks, while subject S14’s EFW was on the 38th percentile at 34 weeks and on
the 8th at 39 weeks. The earliest gestational age of enrollment in the study was at 31+5 weeks,
and this fetus was delivered the following day. The delivery of the other fetuses was relatively
69
evenly distributed over the next eight weeks until term. Fetal MRI in IUGR fetuses was usually
performed shortly after the initial clinical suspicions of growth restriction, with the longest
interval between MRI and delivery being five weeks, and the majority delivered within one to
two weeks of the MRI. Although it is difficult to ascertain exactly when the growth restriction
started in this cohort, it was likely to be during the third trimester, as IUGR is more frequently
found in late gestation (Figueras et al., 2009).
Figure 11 Flow diagram of the study participants in the study. In total, 60 subjects had
newborn brain MRI scan, and 47 of the total 109 subjects participated in the developmental
follow-up. 40 study participants who had complete fetal MRI data (flows and T2s) were
included in the hemodynamic analysis of the study.
70
Table 3. Delivery condition of the 14 IUGR subjects. S06 chose the delivery mode and had a
stillbirth. 7 out of 13 live newborns were admitted to the neonatal intensive care unit (NICU). IUGR
score
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ys
8da
ys
-
3da
ys
0da
ys
1da
y
0da
ys
0da
ys
0da
ys
0da
ys
0da
ys
Apgar
(1min/5min)
9/9
8/9
4/7
9/9
9/9
0/0
9/9
9/9
8/9
8/9
8/9
9/9
7/9
9/9
BirthGA
(Wk+Da
y)
31+6
38+3
36+2
33+5
35+4
33+1
35+1
38+1
37+5
37+3
40+3
40+5
39+1
39+0
Mod
eof
delivery
FailedIOLà
Emg.CS
Sch.CSforIUGR
Sch.CSforIUGR
FailedIOLà
Emg.CS
Emg.CS
Breechassisted
vagina
ldelivery
Emg.CSdu
eto
nuchalcord
FailedIOLà
Em
g.CS
IOLforIUGR
Emg.CSforIUGR
Assis
tedSV
D
FailedIOLà
Em
g.CS
Sch.CSfor
fibroids
Sch.CSfor
breech
Subject
S01
S02
S03
S04
S05
S06
S07
S08
S09
S10
S11
S12
S13
S14
71
To rule out confounding factors for growth and hemodynamic analysis, we made a
comparison of clinical characteristics between the IUGR group and normal group as shown in
Table 4. There were no significant differences in either mean GA (P = 0.6) or maternal age (P =
0.7) at the time of MRI between the two groups. IUGR fetuses were born 2.4 ± 0.8 weeks earlier
than normal fetuses. The mean interval between MRI and birth was 11 ± 13 days for IUGR
fetuses and 21 ± 10 days for normal fetuses (P = 0.01).
Table 4. Characteristics of normal and IUGR group. There was no significant difference in
gestational age when MRI scan was performed between the two groups. IUGR fetuses had
lower estimated fetal weight (EFW) and estimated brain weight (EBW) than normal fetuses.
However, the ratio of EBW/EFW was significantly higher in the IUGR group. GA: gestational
age.
Characteristics Normal (n = 26)
IUGR (n = 14) P values
GA at MRI scan (weeks) 35.9 ± 0.9 35.4 ± 2.4 0.5
Maternal age (year) 33.8 ± 4.5 34 ± 4 0.7
Days from MRI to birth 11 ± 13 21 ± 10 0.01*
EFW at MRI scan (kg) 2.8 ± 0.3 1.9 ± 0.6 0.0001*
EBW at MRI scan (g) 300 ± 29 249 ± 55 0.005*
EBW Z-score 0.02 ± 0.86 -1.36 ± 0.73 <0.0001*
% of EBW over EFW 10.9 ± 1.0 13.8 ± 2.3 0.0004*
GA at Birth (weeks) 39.6 ± 1.1 37.0 ± 2.8 0.008*
Birth weight (kg) 3.16 ± 0.41 1.95 ± 0.64 < 0.0001*
Birth-weight percentile 33 ± 23 2 ± 2 < 0.0001*
72
4.2 Fetal hemodynamics by MRI and ultrasound
4.2.1 Imaging results
4.2.1.1 MRI growth findings
EFW below the 10th percentile for appropriate GA is considered to be SGA. However,
SGA needs to be distinguished from IUGR, because SGA is a simple measure of fetal weight,
whereas IUGR describes a condition in which the fetus is unable to reach growth potential due
to an insufficiency of placental supply. SGA fetuses may be constitutionally small and there
may be AGA fetuses that suffer from placental insufficiency but are unnoticed due to their
unalarming “normal” EFW. In our cohort, all 14 IUGR newborns were SGA at birth. Four
subjects in the normal group also had birth weights below the 10th percentile, but had no
postnatal evidence of growth restriction.
The EFW measured by ultrasound and by MRI on the same day had good agreement (R2
= 0.9, P < 0.0001) (Figure 12). As expected, EFW by MRI, birth weight and birth weight
percentile were significantly lower in the IUGR fetuses compared to the normals. IUGR fetuses
also had lower estimated brain weights (EBW) (P = 0.005) and overall had lower gestational
age-appropriate brain weight Z- scores (P < 0.0001). We observed a higher ratio of EBW over
EFW in the IUGR fetuses (P = 0.0004). This finding indicates asymmetric growth associated
with brain-sparing physiology in the IUGR fetuses. This observation was also confirmed
postnatally when we compared the ratio of HC/birth weight in the two groups. IUGR newborns
had significantly higher HC/birth weight ratios than the normal newborns (P = 0.0005) (Figure
13). Despite the observation that IUGR fetuses seemed to be able to conserve brain growth by
sacrificing somatic growth, the estimated brain weight Z-score was still significantly lower in
the IUGR fetuses compared to the score for normal fetuses. This finding was in keeping with
73
prior studies of IUGR in animal models (Poudel et al 2014). Delayed brain growth may account
for the possible neurodevelopmental outcomes that have been discussed previously.
Figure 12 Estimated fetal weight measured by MRI and ultrasound (U/S). MRI estimated
fetal weight had good agreement with ultrasound estimated fetal weight with R2 = 0.9 and P <
0.0001. Bias = 0.2 ± 0.58.
Figure 13 Comparison of head circumference / birth weight ratio between IUGR and
normal newborns. IUGR newborns had significantly higher ratio of head circumference (HC)
over birth weight compared to normal newborns.
4.2.1.2 MRI hemodynamic findings
During each MRI scan, approximately 20% of PC and T2 measurements were repeated
due to motion artefacts. Despite this, acceptable image quality was obtained in all but one
0 1 2 3 40
1
2
3
4
MRI wt/US wt
MRI wt (g)
U/S
wt (
g)
R2 = 0.90, P <0.0001Y = 1.08*X -0.28
1 2 3 4
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
Average
Diff
eren
ce (M
RI E
FW -
U/S
EFW
) Bland-Altman MRI EFW vs U/S EFW
Normal IUGR0
10
20
30
HC
/birt
h w
eigh
t (cm
/kg)
n = 26 n = 14
P = 0.0005
*
74
subject for all major fetal vessels of interest. The average scan duration was 45 minutes. Post-
processing time included up to one hour for fetal weight and brain weight estimation, 1 to 1.5
hours for metric optimization of PC flow measurements, and 15 minutes to measure vessel T2s.
As discussed earlier, late-onset IUGR is associated with changes in blood flow
distribution in response to hypoxia. Therefore, we would expect to observe different circulatory
patterns in IUGR and normal fetuses. Figure 14a shows a comparison of the MRI-measured
flows in major fetal vessels indexed to EFW. IUGR fetuses appeared to have a higher mean
CVO (518 ± 112 ml/min/kg) compared with the normal fetuses (463 ± 54 ml/min/kg), although
the difference was not significant (P = 0.1). Neither the MPA nor AAo flows were significantly
different in the two groups, but when the ratio of MPA:AAo was calculated, the average ratio
was significantly higher in the IUGR group (1.68 ± 0.52) than in normal fetuses (1.25 ± 0.33, P
= 0.02) (Figure 14b). This finding indicates an exaggerated right-sided dominance of the
cardiac output in IUGR fetuses. IUGR fetuses had significantly increased SVC flow (IUGR:
211 ± 57 ml/min/kg, normal: 128 ± 35 ml/min/kg, P < 0.0001) in keeping with the brain-sparing
physiology observed in animal models. We observed higher DA flow (P = 0.02), and lower PBF
(P = 0.01) in the IUGR fetuses. In seven out of 14 IUGR fetuses, SVC flow was higher than
AAo flow, which would suggest a proportion of DA flow passed retrograde around the aortic
arch to support the increase in cerebral blood flow. In addition to the circulatory redistributions
around the heart, IUGR fetuses had significantly lower UV blood flow (105 ± 26 ml/min/kg)
compared to normal fetuses (134 ± 29 ml/min/kg, P = 0.004), suggesting higher placental
resistance in IUGR that was possibly due to placental vasculopathy. In the most severe cases of
IUGR, the circulatory redistribution was dramatic, with an approximate doubling of cerebral
blood flow (S01 – S07) and halving of UV flow (S01, S06, S07, and S10). This finding is in
keeping with the adaptive physiology in response to acute hypoxia previously shown in fetal
75
lambs and by conventional cordocentesis oximetry and Doppler in human IUGR fetuses (Cohn
et al., 1974; Hecher et al., 1995).
a)
b)
Figure 14 MRI measured major vessel flows in the IUGR and normal fetuses. a) IUGR
fetuses showed flow redistribution: high SVC flow and low PBF. Low UV flow indicated
possible placental insufficiency. b) The average ratio of MPA and AAo in IUGR fetuses is
higher than in normal fetuses. (CVO: combined ventricular output; DA: ductus arteriosus; PBF:
pulmonary blood flow; MPA: main pulmonary artery; AAo: ascending aorta; SVC: superior
vena cava; DAo: descending aorta; UV: umbilical vein.)
Since the placenta is the gas exchange organ for the fetus, oxygenation of the fetal blood
0
200
400
600
800
Flow
(ml/m
in/k
g)
CVO DA PBF MPA AAo SVC DAo UV
IUGRNormal
* ** *
P=0.1 P=0.05 P=0.6 P<0.0001P=0.02 P=0.9P=0.01 P=0.004
Normal IUGR0
1
2
3
4
Rat
io o
f MP
A: A
Ao
P = 0.02*
76
would be affected in IUGR pregnancies when there was insufficient oxygen transfer from
maternal blood to fetal blood. In most cases, IUGR fetuses are subjected to hypoxia due to
placental dysfunction (Rurak et al., 1990). In this study, we observed that human IUGR fetuses
had lower mean T2 values in all measured vessels (Figure 15), corresponding to lower
calculated blood SaO2 throughout the circulation, and ultimately translating to a hypoxic fetal
state. Lower UV SaO2 in the IUGR fetuses was in keeping with insufficient gas exchange at the
placenta. Together with lower UV flow as shown above, DO2 in IUGR fetuses was calculated to
be lower than normal fetuses (Figure 16) (normal: 20.9 ± 4.2; IUGR 13.9 ± 4.2, P < 0.0001).
Studies in ovine fetuses with acute fetal hypoxia have shown that despite the reduction of DO2,
fetal VO2 can be variably maintained by increasing OEF in the setting of DO2 reductions of up
to 50% (Itskovitz, 1983). Therefore, we were interested to see if we would observe similar
findings in the human fetus by using MRI. We found that IUGR fetuses had significantly higher
OEF (40% ± 10%) than normal fetuses (34%± 8%, P = 0.03). However, IUGR fetuses had lower
VO2 compared to the normal fetuses (normal: 6.9 ± 1.7; IUGR: 5.5 ± 1.7, P = 0.02). This
observed reduction in VO2 in our IUGR fetuses in our study may be associated with decreased
movement and growth in chronic placental insufficiency (Soothill, 1987; Richardson &
Bocking, 1998). Thus, even though the compensatory increase in OEF would maintain VO2 in
acute hypoxia, it seems that in chronic hypoxia, the compensation could be inadequate, and
result in slowing down of fetal growth.
77
Figure 15 T2 relaxation time in major vessels in normal and IUGR fetuses. IUGR fetuses
had significantly lower T2 in all measured vessels. (MPA: main pulmonary artery; AAo:
ascending aorta; SVC: superior vena cava; DAo: descending aorta; UV: umbilical vein.)
Figure 16 Calculated oxygen consumption (VO2) and oxygen delivery (DO2) in IUGR and
normal fetuses. IUGR fetuses had significantly lower unindexed VO2 and DO2 than normal
fetuses. Similar findings were observed when VO2 and DO2 were indexed to the fetal weight.
0
50
100
150
200
250
T2 (m
s)
MPA SVC DAo UVAAoNormal IUGR
* ** **P<0.0001P=0.002 P=0.0002P=0.003 P=0.002
0
10
20
30
0
20
40
60
80
100
VO2
(ml/m
in)
P < 0.0001
DO
2 (ml/m
in)
P < 0.0001
NormalIUGR
Unindexed VO2 and DO2
0
5
10
15
0
10
20
30
40
VO2
(ml/m
in/k
g)
P = 0.0009
DO
2 (ml/m
in/kg)
P = 0.0003
IUGR Normal
Indexed VO2 and DO2
78
4.2.1.3 Doppler findings
According to the Royal College of Obstetricians and Gynaecologists, UA Doppler is the
primary ultrasound surveillance tool in IUGR pregnancies, especially in early-onset IUGR.
Even though many studies have shown that reduced PI in the MCA and low CPR are also
associated with poor perinatal outcome (Severi et al., 2002; Hershkovitz et al., 2000; Bahado-
Singh et al., 1999), these two parameters are not routinely measured in low risk pregnancies. In
the normal group, 11 out of 26 subjects underwent CPR measurement only as part of the
research ultrasound on the same day as the MRI. 15 out of 26 had at least one clinical CPR
measurement after 30 weeks’ gestation. In the IUGR group, two out of 14 subjects only had
CPR measurement in the research ultrasound study performed on the same day as the MRI scan.
The remaining 12 subjects had at least one and up to eight CPR measurements during clinical
scans. Collectively, the Doppler results with the lowest gestational age-appropriate CPR
percentile were recorded for each subject. As shown in Table 5, IUGR and normal fetuses were
at a similar gestational age when the lowest CPR percentile was recorded. We expected a higher
UA PI in the IUGR group as an indicator of higher vascular resistance in the abnormal placenta.
However, the slightly higher UA PI observed in the IUGR fetuses was not significantly different
from that of the normal groups (P = 0.08). Contrastingly, MCA PI (P = 0.04) and CPR (P =
0.005) were significantly lower in the IUGR group compared to normals, in keeping with
cerebral vasodilation and brain-sparing physiology.
79
Table 5. Doppler ultrasound findings in normal and IUGR fetuses. IUGR fetuses had
significantly lower CPR and MCA PI compared with normal fetuses.
GA of meas. UA PI MCA PI CPR
Normal 35.7 ± 1.0 0.99 ± 0.23 1.61 ± 0.32 1.68 ± 0.35
IUGR 36.3 ± 3.1 1.22 ± 0.38 1.39 ± 0.29 1.24 ± 0.44
P values 0.5 0.08 0.04* 0.005*
4.2.2 Placental histology
12 of the 14 IUGR subjects had classical histopathologic findings associated with IUGR
(placental weight below 10th percentile; multifocal infarction; decidual vasculopathy). The two
IUGR subjects whose placentas did not meet these criteria had milder placental abnormalities
(one had placental weight in the 10th – 25th centile with mild dysmaturity of chorionic villi and
over- coiling of the umbilical cord; the other had over-coiling of the cord and increased villous
vascularity with placental weight in the 25th -50th centile). However, many of the placentas in
the normal group also had mild histologic features of IUGR, as described in previous studies
(Redline, 2008). Of the 17 available non-IUGR placentas, four were below the 10th weight
percentile, but none had severe lesions, such as multifocal infarction or decidual vasculopathy.
Nearly all had subtle abnormal findings (e.g., chorangiosis, villitis, villous dysmaturity,
meconium staining, etc.). As Salafia et al. (1992) have described, there is poor association
between conventional placental histology and clinical features of IUGR. Therefore, the presence
of only mild histological abnormalities in IUGR placentas, as well as the presence of histologic
abnormalities and small sizes of some of the non-IUGR placentas, should not be unexpected.
80
4.2.3 Correlations
We analyzed the correlations between the severity of late-onset IUGR with ultrasound
and MRI parameters. According to our composite scoring system, an increased IUGR score
denotes increased severity of growth restriction. As shown in Figure 17, higher IUGR scores
were associated with higher UA PI (R2 = 0.20, P = 0.01), indicating higher placental vascular
resistance. Fetuses with more severe growth restriction tended to have lower MCA PI, which
suggests reduced cerebral vascular resistance; however, the association did not reach statistical
significance. CPR, which takes into account both placental and cerebral vascular resistance, was
negatively associated with severity of IUGR (R2 = 0.26, P = 0.001), as expected.
Figure 17 The association of IUGR score with Doppler parameters. CPR was negatively
associated with IUGR severity score, and umbilical artery pulsatility index (UA PI) was
positively associated with IUGR score. More severe IUGR tended to have lower middle cerebral
artery pulsatility index (MCA PI). However, the association was not significant.
The relationships between the IUGR scores and MRI parameters are shown in Figure
18. We observed that increased IUGR severity was associated with decreased DO2 (R2 = 0.48, P
< 0.0001), in keeping with the known decreased placental supply in the growth restricted
pregnancies. This coincided with the observation that more severe IUGR fetuses had higher
placental resistance suggested by the lower blood flow in the UV (R2 = 0.28, P = 0.002), and
0 1 2 3 4 50.0
0.5
1.0
1.5
2.0
2.5CPR
IUGR Score
R2 = 0.26 P = 0.001
0 1 2 3 4 50.0
0.5
1.0
1.5
2.0
2.5MCA PI
IUGR Score
R2 = 0.09 P = 0.07
0 1 2 3 4 50.0
0.5
1.0
1.5
2.0UA PI
IUGR Score
R2 = 0.20 P = 0.01
81
insufficient gas exchange at the placenta suggested by the lower UV T2 (SaO2). In addition,
increased IUGR scores were associated with lower VO2, which indicates a slowing of fetal
metabolism in response to the decreased DO2. Furthermore, increased SVC flow was associated
with more severe IUGR (R2 = 0.52, P < 0.0001). This MRI evidence of brain-sparing was not
detected by conventional MCA Doppler (Figure 18). Finally, fetuses with more severe IUGR
had a higher ratio of EBW/EFW, indicating asymmetrical growth restriction.
Figure 18 The association of IUGR score with MRI parameters. Several MRI parameters
had strong associations with IUGR score. Ambiguous IUGR score due to missing data were not
included in this analysis. (DO2: oxygen delivery; VO2: oxygen consumption; SVC: superior
vena cava; UV: umbilical vein.)
0 1 2 3 4 50
10
20
30
40DO2
ml/m
in/kg
IUGR Score
R2 = 0.48 P < 0.0001
0 1 2 3 4 50
50
100
150
200
250UV T2
IUGR Score
ms
R2 = 0.42 P < 0.0001
0 1 2 3 4 50
2
4
6
8
10VO2
ml/m
in/kg
IUGR Score
R2 = 0.17 P = 0.02
-3
-2
-1
0
1
2Brain Z Score
IUGR Score
R2 = 0.35 P = 0.0004
0 2 3 4 51
0 1 2 3 4 50
100
200
300
400SVC flow
ml/m
in/kg
R2 = 0.52 P < 0.0001
IUGR Score
0 1 2 3 4 50
5
10
15
20Brain %
IUGR Score
R2 = 0.49 P < 0.0001
82
Figure 19 Association of brain weight with CPR and the flow in the superior vena cava
(SVC). (a) Brain weight was positively associated with ultrasound-based cerebral-placental
ratio. (b) Brain weight was negatively associated with SVC flow.
We found a 23% reduction in absolute CDO2 (p=0.01) and a 17% reduction in brain
volume (p=0.005) in fetuses with IUGR, although there was no significant difference in CDO2
indexed to brain volume. We observed a negative association between CPR and EBW (R2 =
0.26, P = 0.001). In agreement with the positive association we found between EBW and UV T2
(R2 = 0.22, P = 0.002) and DO2 (R2 = 0.14, P = 0.01), these findings support the hypothesis that
cerebral oxygen delivery is associated with fetal brain growth and development (Figure 19).
Intuitively, a bigger brain should have more cerebral blood flow. However, we observed that
higher blood flow in the SVC was associated with smaller EBW but higher EBW/EFW ratio.
This finding is in keeping with the concept that despite brain sparing physiology, placental
insufficiency ultimately affects brain growth.
We also found the relationship between birth weight Z-score and the following MRI
parameters: SVC flow (R2 = 0.42, P < 0.0001), UV T2 (R2 = 0.39, P < 0.0001), DO2 (R2 =
0.15, P = 0.01). VO2 was significantly negatively associated with IUGR score but not with birth
weight Z-score. We also found that low UV T2 (i.e., low UV SaO2) was associated with high
0.0 0.5 1.0 1.5 2.0 2.50
100
200
300
400
CPR
Bra
in W
eigh
t (g)
R2 = 0.26, P = 0.001
0 100 200 300 4000
100
200
300
400
SVC flow (ml/min/kg)
Bra
in W
eig
ht (
g)
R2 = 0.31 P = 0.0002
(a) (b)
83
SVC flow (R2 = 0.26, P = 0.0009) (Figure 20), which is another illustration of how insufficient
placental gas exchange is associated with brain-sparing.
Figure 20 Association between T2 in the umbilical venous blood with blood flow in the
superior vena cava (SVC). MRI measured UV T2 and SVC flows are negatively associated.
We compared our MRI hemodynamic and biometric indices of fetal growth restriction
with more conventional ultrasound markers. As CPR has consistently been shown to be the
superior Doppler parameter for identifying late-onset IUGR, we correlated this with various
MRI measures. We performed this analysis for the lowest or “worst” CPR recorded during the
late gestational period, and using the CPR recorded at the same time as the MRI. Overall, there
was good association between the two techniques. As a measure of placental and cerebral
vascular resistance, when CPR decreased, so did UV T2 (R2 = 0.12, P = 0.03) and DO2 (R2 =
0.31, P = 0.0003), while SVC flow increased (R2 = 0.26, P = 0.0009) (Figure 21). UA PI was
positively associated with SVC flow (R2 = 0.18, P = 0.006) and inversely related to UV T2 (R2
= 0.16, P = 0.01) and DO2 (R2 = 0.29, P = 0.0003) (Figure 22). Both MCA PI and SVC flow
are indicators of cerebral vascular resistance, and they were shown to be positively related (R2 =
0.16, P = 0.02).
0 50 100 150 200 250
100
200
300
400
UV T2 (ms)
SV
C fl
ow
(ml/m
in/k
g) R2 = 0.26
P = 0.0009
84
Figure 21 Association between CPR and blood flow in the superior vena cava (SVC). MRI-
measured SVC flow and CPR were negatively correlated.
Figure 22 Association between oxygen delivery (DO2) and umbilical artery pulsatility
index (UA PI). Calculated DO2 was negatively associated with UA PI.
We also correlated MRI parameters with the research Doppler parameters that were
obtained on the same day as the MRI scan. Instead of the lowest CPR, the CPR obtained on
MRI day that was below the 5th percentile was used as an IUGR scoring criterion. This did not
change the allocation of subjects into IUGR or non-IUGR groups. However, the correlation
0.0 0.5 1.0 1.5 2.0 2.50
100
200
300
400
CPR
SV
C fl
ow
(ml/m
in/k
g)
R2 = 0.26 P = 0.0009
0.0 0.5 1.0 1.5 2.00
10
20
30
40
UA PI
DO
2 (m
l/min
/kg)
R2 = 0.29 P = 0.0003
85
between MRI measurements with Doppler measurements was less significant: CPR was
associated with UV flow but not with other MRI parameters; UA PI was associated with SVC
flow (R2 = 0.12, P = 0.03), DO2 (R2 = 0.27, P = 0.001) and UV flow (R2 = 0.20, P = 0.006);
MCA PI did not correlate with any MRI hemodynamic measures. This finding indicates that the
“lowest” CPR could be a better indicator of late-onset IUGR than the CPR collected on the day
of MRI. One explanation for this finding is the resolution of blood flow distribution in the
setting of chronic hypoxia. Our data would suggest that an improvement in CPR in the setting of
late-onset IUGR is more likely due to fetal metabolic adaptation to chronic hypoxia, than
resolution of the placental insufficiency.
4.2.4 Performance of MRI and Doppler
Having established a good agreement between our MRI and conventional Doppler
measures of IUGR, we were interested in comparing the performance of the two modalities for
identifying IUGR. Five fetuses (S08, S11–S14) had normal Dopplers and normal flow
distribution by MRI, but met criteria for IUGR by fetal growth, placental histology and neonatal
anthropometric parameters. However, all of these fetuses had reduced SaO2 and DO2 by MRI,
providing evidence of a placental cause of IUGR and support for the sensitivity of fetal MR
oximetry as a parameter of placental insufficiency.
We used ROC curves to analyze the performance of the two techniques. In order to
avoid bias towards Doppler, we only used the three post-natal criteria (low birth weight or drop
in EFW percentile, low Ponderal index, and placental histopathology) in our IUGR scoring
system as the “gold-standard” to identify IUGR. When defining the IUGR subjects based solely
on postnatal evidence, there were 12 IUGR and 28 normal fetuses. Figure 23a illustrates the
ROC plots for MRI (SVC flow, UV T2 and DO2) and Doppler measurements for the
86
identification of IUGR. Among the six parameters we were interested in, SVC flow had the
highest area under the curve (AUC) (0.94, 95% CI: 0.87 – 1.00, P < 0.0001), and UA PI had the
lowest AUC (0.73, 95% CI: 0.53 – 0.93, P = 0.02). Even though CPR is considered to be the
more sensitive measure of fetal hypoxia in animal and clinical models, correlating better with
postnatal outcome, the AUC of CPR (0.8, 95% CI: 0.64 – 0.91, P = 0.003) was shown to be
lower than any of the three MRI parameters. However, the differences between the AUCs in
MRI and Doppler parameters were not significant.
We also compared the performance of the lowest CPR during late pregnancy to the CPR
measured on the same day the MRI scan was performed (Figure 23b) with regards to the
identification of IUGR based on postnatal evidence. The lowest CPR after 30 weeks had an
AUC of 0.8 (95% CI: 0.64 - 0.91, P = 0.003). On the other hand, the CPR measured the same
day as the MRI had an AUC of 0.67. As discussed above, chronic hypoxia can result in fetal
metabolic adaptation to hypoxia resulting in the normalization of the fetal circulatory
redistribution that occurs during acute hypoxia (Richardson & Bocking, 1998). Due to this
normalization of flow pattern, the typical Doppler findings in IUGR pregnancies may disappear.
In our study 8/14 IUGR fetuses had improved UA PI and 4/14 had improved CPR from 32
weeks to 38 weeks. Therefore, the presence of an abnormally low CPR at any time in late
pregnancy appears to be a reliable indicator of IUGR, even if it seems to be normalized later on.
87
(a) (b)
Figure 23 ROC curves for MRI and Doppler measurements for identification of IUGR. a)
ROC curves for MRI and lowest Doppler measurements for identification of IUGR. MRI
parameters had overall larger area under the curve than Doppler parameters. b) ROC curves for
lowest CPR and MRI day CPR for identification of IUGR. The lowest CPR had a larger area
under the curve than CPR obtained on the same day when MRI scan was performed.
4.3 Neurodevelopment in late-onset IUGR
4.3.1 Fetal brain oxygenation
As described above, we found profound reductions in fetal DO2 and VO2 in the IUGR
fetuses. Brain-sparing physiology resulted in smaller, but still significant reductions in fetal
CDO2 (Figure 24). When we compared the percentage of unindexed CDO2 to unindexed total
body DO2, IUGR had significantly higher proportion of DO2 supplying the brain (P < 0.0001).
Furthermore, a higher ratio of CDO2/DO2 correlated with a higher EBW:EFW ratio. Cerebral
OEF, which is calculated as CVO2/CDO2, was higher in the IUGR group (IUGR: 29% ± 14%;
normal: 25% ±7%) and although the difference was not statistically significant (P = 0.3), it
would explain the non-significant difference in fetal CVO2, despite the lower CDO2 in IUGR
0 50 1000
50
100
100% - Specificity%
Sens
itivi
ty%
UV T2
UA PI
DO2
SVC flow
CPRMCA PI
0 50 1000
50
100
100% - Specificity%
Sens
itivi
ty%
lowest CPR
MRI day CPR
88
fetuses. In summary, higher SVC flow and cerebral OEF in IUGR fetuses result in preservation
of CVO2 in the setting of IUGR.
Figure 24 Cerebral oxygen consumption (CVO2) and cerebral oxygen delivery (CDO2) in
normal and IUGR newborns. IUGR fetuses had lower total fetal cerebral oxygen delivery and
similar CDO2 indexed to brain weight compared with normal controls.
4.3.2 Neonatal brain MRI
In order to investigate the impact of the reductions in cerebral oxygen delivery we
observed in IUGR fetuses on brain development, we attempted to perform neonatal brain MRI
and neurodevelopmental testing on all of our subjects. 15 IUGR subjects and 45 normal subjects
(IUGR identified based on low birth weight and abnormal Doppler) underwent neonatal brain
MRI soon after birth. We were unable to conduct neonatal MRI in 5 of the IUGR newborns due
to concerns on the part of their families and physicians about the safety of them being brought to
SickKids from Mount Sinai for a research study. However, all 5 of these subjects had normal
findings on brain ultrasound. Most of the scans were performed within two weeks of birth. One
IUGR infant was scanned at 45 weeks corrected gestational age, and one at 47 weeks. Despite
this, the mean corrected gestational age was 40 weeks for both groups (P > 0.9).
0
10
20
30
0
20
40
60
80
CVO
2 (m
l/min
)
P = 0.3
CD
O2 (m
l/min)
P = 0.01
IUGR Normal
Unindexed CVO2 and CDO2
*0
2
4
6
8
0
5
10
15
20
CVO
2 (m
l/min
/100
g)
P = 0.3
CD
O2 (m
l/min/100g)
P = 0.7
Indexed CVO2 and CDO2
IUGR Normal(a) (b)
89
IUGR newborns had lower brain weight Z-scores compared to normal newborns (p <
0.05) (Figure 25). There were no major abnormalities on brain imaging in either group on
conventional brain MRI. Four of the IUGR fetuses had diffuse excessive high signal intensity
(DEHSI) of the white matter, which was found in none in the normal group.
On MRS, five of 11 IUGR subjects and six of 28 normal infants had lactate in the basal
ganglia. However, the difference in the proportion was not statistically significant (P = 0.2). A
slightly higher basal ganglia NAA-to-choline ratio was observed in the IUGR group (0.65 ±
0.07) compared to the normal group (0.61 ± 0.14), but the difference did not reach significance
(P = 0.2). In addition, we found no difference in NAA-to-choline ratios between the two groups
in the anterior frontal white matter (P = 0.7).
Figure 25 Brain weight Z-score in IUGR and normal newborns. Compared with normal
newborns, IUGR newborns had smaller brain weight Z-score.
We found a significant positive correlation between corrected gestational age and FA,
and a negative correlation between corrected gestational age and ADC in both anterior frontal
white matter and basal ganglia in the normal group (Figure 26). When IUGR fetuses were
-1
0
1
2
3
Z sc
ore
Newborn brain Z score
Normal IUGR
P = 0.007
Newborn brain weight Z score
90
compared with controls, we found significant reductions in basal ganglia and mean white matter
FA in the IUGR fetuses (Figure 27). When we investigated the relationships between fetal
hemodynamic parameters and quantitative measures of brain development on neonatal brain
MRI, we found a significant association between fetal CDO2 and neonatal brain weight Z-score
(R2 = 0.15, p = 0.003) (Figure 28). We found no significant correlations between fetal
hemodynamic and neonatal DTI or MRS measures.
Figure 26 Association of fractional anisotropy (FA) and apparent diffusion coefficient
(ADC) in thalamus and anterior white matter (WM) with corrected gestational age (GA).
(a) Anterior WM FA at centrum semiovale was positively associated with corrected GA. (b) FA
in thalamus was positively associated with corrected GA. (c) Anterior WM ADC at centrum
semiovale was negatively associated with corrected GA. (d) ADC in thalamus was negatively
associated with corrected GA.
35 40 45 500.0
0.1
0.2
0.3
Anterior WM FA with GA
corrected GA
FA
IUGR(R2=0.09, P = 0.4)
Normal (R2=0.4, P = 0.0004)
35 40 45 500.0
0.1
0.2
0.3
Thalamus FA correlation with GA
corrected GA
FANormal (R2=0.47, P < 0.0001)IUGR (R2=0.20, P = 0.2)
35 40 45 501.0
1.2
1.4
1.6
1.8
2.0
2.2
Anterior WM ADC with GA
corrected GA
AD
C
IUGR (R2=0.10, P = 0.4)
Normal (R2=0.41, P = 0.0003)
35 40 45 500.9
1.0
1.1
1.2
1.3
corrected GA
AD
C
IUGR(R2=0.51, P = 0.02)
Normal (R2=0.37, P = 0.0008)
Thalamus ADC correlation with GA
(c) (d)
(a) (b)
91
Figure 27 Fractional anisotropy (FA) in white matter and basal ganglia in normal and IUGR
newborns. IUGR newborns had lower FA in both white matter and basal ganglia compared to
normal newborns.
Figure 28 Association between net fetal cerebral oxygen deliver and neonatal brain weight
Z-score. There is a positive association between unindexed fetal cerebral oxygen delivery and
newborn brain weight Z-score (R2 = 0.15, p = 0.003).
0.0
0.1
0.2
0.3
0.4FA
white matter FA
Normal IUGR
P = 0.03
0.15
0.20
0.25
BG
FA
Normal IUGR
P = 0.04
basal ganglia FA
0 20 40 60 80 100-1
0
1
2
3
unindex CDO2 (ml/min)
new
born
bra
in Z
sco
re
R2= 0.15, P = 0.003
92
4.3.3 Developmental follow-up
At the current stage of the project, the developmental follow-up data for this cohort is
incomplete. However, significant results have already emerged. Table 6 shows the preliminary
findings of the developmental outcomes of the IUGR and normal infants at four, eight, 12 and
18 months of age. IUGR newborns had lower scores compared to the normal newborns for the
majority of the developmental domains tested. However, only the gross motor score by AIMS
measured in normal infants at eight months’ and 12 months’ old are significantly lower in the
IUGR group. This difference in motor function was no longer statistically significant on the
Bayley III test of infant development performed at 18 months. The gap between the IUGR
subjects and controls in terms of height, weight and head circumference also narrowed over
time, such that there were no longer statistically significant at 18 months of age (corrected for
the gestational age at birth) (Figure 29).
Figure 29 Postnatal anthropometric indices in IUGR and control subjects. The gap between
the height, weight and head circumferences of the two groups narrowed with increasing
intervals from the IUGR (* indicates significant difference)
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Table 6. Developmental outcome in IUGR and normal infants. IUGR infants had lower
scores in the Alberta Infant Motor Scale (AIMS) than those of normal infants at eight months of
age. * indicates statistically significant results
Months Normal IUGR Pvalue
4 AIMS 15.85±4.13(n=26) 14.71±2.56(n=14) 0.3 FineMotor 54.15±6.29(n=26) 52.21±7.72(n=14) 0.4
8 AIMS 41.43±7.84(n=23) 34.14±10.36(n=14) 0.03* FineMotor 47.07±4.62(n=23) 45.57±11.81(n=14) 0.09 Social 25.35±6.10(n=23) 25.07±4.97(n=14) 0.7
12 AIMS 55.04±3.11(n=23) 48.57±8.11(n=14) 0.01* FineMotor 63.24±2.68(n=17) 61.91±2.02(n=11) 0.1 Social 39.36±5.92(n=22) 37.38±6.27(n=13) 0.4
18
(BayleyScales)
CognitiveScore 107.5±2.46(n=18) 100.5±11.06(n=11) 0.1
CognitiveRank 64.50±24.49(n=18) 50.45±22.37(n=11) 0.3
Language-Reception 11.33±3.74(n=18) 9.27±4.69(n=11) 0.1
Language-Expression 10.78±3.25(n=18) 9.27±4.56(n=11) 0.4
Language-Rank 62.54±30.35(n=18) 40.55±40.35(n=11) 0.1
FineMotor 11.61±1.88(n=18) 11.09±1.89(n=11) 0.8 GrossMotor 9.94±1.47(n=18) 9.55±2.81(n=11) 0.8 Motor-Rank 61.06±19.32(n=18) 63.8±15.89(n=11) 0.7
94
5 Discussion Late-onset IUGR is associated with many short term adverse outcomes including high
incidences of cesarean section, still birth, neonatal death, as well as long-term developmental
outcome such as cerebral palsy and learning deficits and a preponderance towards
cardiovascular disease in adulthood (Figueras et al., 2015; Baschat et al., 2000; Wang et al.,
2015). In this study, MRI and ultrasound measurements of fetal hemodynamics and biometry in
late-onset IUGR pregnancies were compared with those of normal fetuses. Our MRI parameters
of biometry and fetal circulatory adaptation to placental insufficiency are concordant with
conventional ultrasound measurements, especially CPR. While the changes we observed in
cerebral and placental vascular resistance are well documented by Doppler ultrasound in late-
onset IUGR (Backe & Nakling, 1993; DeVore, 2015; Flood et al., 2014), our demonstration of
human fetal circulatory redistribution has previously only been shown in fetal lambs using
invasive techniques (Cohn et al., 1974). Furthermore, our study revealed that up to a third of
fetuses with postnatal evidence of late-onset IUGR would be overlooked by even the most
sophisticated Doppler methods currently in use. Our findings would suggest that this is because
chronic metabolic adaptation to placental insufficiency tends to normalize fetal flow
distribution, and therefore Doppler findings. This finding may explain consistent challenges
associated with accurate identification of late-onset IUGR fetuses. Importantly, these fetuses
appear to be identified by MRI because they are hypoxemic.
With regards to the impact of late-onset IUGR on brain development, our study
establishes two important findings which have previously been suspected based on animal
models, but difficult to prove in human pregnancies:
1. despite brain-sparing physiology, placental insufficiency is associated with a reduction
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in fetal cerebral oxygen delivery
2. these reductions in fetal cerebral oxygen delivery are associated with reductions in brain
growth and neurodevelopmental outcome.
Finally, our follow-up neurodevelopmental testing and measures of head circumference
indicate that there may be the potential for catch-up growth and development following late-
onset IUGR. This final observation is a key consideration for the clinical implications of our
results. While our data suggest that late-onset IUGR does indeed have a negative impact on late
gestational brain development, the potential benefit of early delivery from fetal hypoxia needs to
be weighed up carefully against the potential harms of late premature delivery. Our research has
provided important information towards defining the optimal timing of delivery in the setting of
IUGR by providing evidence of a link between reduced cerebral oxygen delivery and neonatal
brain development and subsequent neurodevelopmental outcome. However, while our
demonstration of a narrowing of the difference in neurodevelopmental performance and head
growth with increasing intervals from the fetal growth restriction provides some reassurance
about the potential for postnatal factors to mitigate the impact of IUGR, more detailed long term
neuropsychological and brain imaging investigations may confirm more permanent effects of
the adverse intrauterine environment. Our results also warrant further discussion of the
following areas.
5.1 IUGR hemodynamic and oxygenation The direct assessment of fetal oxygenation with MRI could provide a means of detecting
chronic hypoxia without flow redistribution, thereby potentially enhancing the diagnosis of late-
onset IUGR. In the most severe examples of IUGR, the circulatory redistribution was dramatic.
Seven IUGR fetuses had nearly doubled cerebral blood flow, and four of the seven had half of
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the UV blood flow when compared with our previously published reference ranges in normal
fetuses (Prsa et al., 2014). This finding is consistent with the results of circulatory redistribution
observed in fetal lamb studies that during hypoxia, SVC blood flow increased from 2.6% of the
CVO to 4.1% (Cohn et al., 1974). In contrast to Cohn et al.’s finding of reduced CVO during
acute hypoxia, we observed a slightly higher CVO in the IUGR fetuses, primarily due to
increased output from the right side of the heart. Similar elevated CVO was also observed by
Rurak et al. (1990) and Bernstein et al. (1988) in animal models of chronic fetal hypoxia. This
difference can be explained by the different hemodynamic adaptation to acute and chronic
hypoxia. CVO is the product of heart rate and stroke volume. In acute hypoxia, increased
activity in the parasympathetic efferent nerves leads to a reduction in heart rate. Therefore, CVO
decreases if stroke volume is unchanged or decreased (Rurak et al., 1990). In fetal lambs, it has
been shown that heart rate initially drops but then returns to baseline, which is thought to be
associated with higher concentrations of catecholamines (Jones & Robinson, 1975). Moreover,
sustained hypoxia has been shown to increase the fetal hemoglobin concentration (Teitel et al.
1985; Bernstein et al. 1988). Both increased CVO and hemoglobin concentration would help
increase the blood oxygen carrying capacity to compensate for the reduced DO2 from the
placenta. Therefore, the oxygen supply to the fetus can be maintained to a certain extent.
We also confirmed that placental dysfunction related to late-onset IUGR is associated
with hypoxemia by demonstrating lower overall vessel SaO2 in IUGR fetuses, compared with
normal fetuses as shown by Hecher et al. (1995). The reduced DO2 shown in our results is in
keeping with compromised placental function. VO2 was also lower in the IUGR fetuses,
indicating fetal metabolic adaptation has occurred, although the difference in VO2 appeared to
be smaller than the difference in DO2. This is likely due to increased fractional extraction of
oxygen. Therefore, we would hypothesize that if we compared the blood gas results of IUGR
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and normal fetuses, we would observe a larger oxygen gradient between the umbilical vein and
the umbilical artery in the IUGR group, as shown in animal models (Rurak et al., 1990). This
decreased VO2, together with possibly increased hemoglobin concentration, would contribute to
the normalization of the flow patterns in chronic hypoxia (Richardson & Bocking, 1998).
DO2 is determined by umbilical vein blood flow and the oxygen content of the umbilical
vein blood. The placenta separates the oxygen exchange process into three compartments:
maternal, placental and fetal. Therefore, fetal DO2 could drop when there is dysfunction in any
of these three compartments. The majority of the IUGR cases are due to placental dysfunction
when there is decreased oxygen delivery from the maternal circulation to the placenta,
interference in oxygen diffusion from maternal blood to fetal blood at the placenta or decreased
umbilical blood flow due to increased placental resistance. Our findings have supported these
potential causes of growth restriction as IUGR fetuses had both lower UV blood flow and lower
UV oxygen saturation. Under normal placental function, growth restriction may also occur when
umbilical blood flow is reduced due to poor fetal cardiac function.
5.1.1 Comparison with growth restriction in congenital heart block
By performing MRI scans using the same method described in this project, we also
studied fetuses with congenital heart disease. Among those, Ebstein’s Anomaly and congenital
heart block are associated with low CVO due to poor function of the right side of the heart or
low ventricular contraction rate, respectively (Zhu et al., 2015). Interestingly, these fetuses also
had IUGR. In our recently published case report (Zhu et al. 2015), we demonstrated such a case
with congenital heart block. This fetus had a ventricular rate of about 50 beats per minute, which
was only one-third of a normal fetal heart rate. The EFW was at the 40th centile at 20 weeks’
gestation. The fetus was delivered by cesarean section for non-reassuring ultrasound
98
assessments at 36 weeks’ gestation. By the time the baby was born, the baby’s weight had
dropped to below the 3rd percentile. In this case, the fetal CVO was 238 ml/min/kg, which is
about half the normal fetal CVO we found in a large group of control subjects (Prsa et al.,
2014). Despite an increase of about 70% in stroke volume, the significant reduction in CVO
resulted in diminished umbilical flow. However, a normal proportion of umbilical flow in CVO
(35% compared with 29% ± 9% (Prsa et al., 2014)) and a normal UV T2 (194ms compared with
normal mean 192 ± 29ms in this study) indicated normal placental function in this fetus. Due to
the low UV flow, DO2 (13.3 ml/min/kg) was at the 4th percentile of the normal range, very
similar to the IUGR fetal DO2 we demonstrated in this study. On the other hand, VO2 was
unaffected by the bradycardia, and was achieved by increased oxygen extraction (Zhu et al.,
2015). Interestingly, brain-sparing was also observed in this heart block fetus, with the SVC
flow accounting for 47% of the CVO, which is significantly higher than that in normal fetuses
(reference range 15% to 43%, Prsa et al., 2014). As a result, the EBW:EFW ratio was 13.7%,
which is very similar to the ratio in our IUGR group (13.8% ± 2.3%). The asymmetrical growth
was also confirmed postnatally, with a high ratio of head circumference over birth weight.
Although the use of prenatal steroids, a treatment for heart block, could also contribute to the
overall slowing down of fetal growth, the asymmetrical growth was evidence of hemodynamic
adaptation to low cardiac output. In many aspects, this heart block fetus with normal placental
function resembled our IUGR fetuses who had placental insufficiency, but through a different
hemodynamic mechanism.
5.1.2 Ultrasound and MRI in IUGR detection
Many studies (Figueras et al., 2009; Baschat et al., 2000; Boers et al., 2010) have
suggested that identification of IUGR solely relying on EFW is problematic, because a large
proportion of SGA fetuses are constitutionally small. In pregnancies suspected to be
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complicated by IUGR, current management includes closer monitoring of the fetal condition
(Lausman & Kingdom, 2013). However, whether or not frequent late pregnancy
ultrasonography should be applied to all third-trimester pregnancies is still questionable due to
the lack of evidence showing the benefit of doing so. In a recently published prospective cohort
study with 3,977 third-trimester singleton pregnant subjects, Sovio et al. (2015) investigated the
effectiveness of universal ultrasound (routine third-trimester ultrasound in all pregnancies,
regardless of pre-pregnancy risk) in identifying increased risk of adverse perinatal outcome. The
study demonstrated that selective ultrasound monitoring in late gestation detected 20% of all
SGA infants that were born; whereas additional late gestation monitoring detected 57%. Among
the SGA neonates, those with the lowest abdominal circumference growth rate had the highest
risk for neonatal morbidity (relative risk 3.9, 95% CI 1.9 to 8.1).
However, this tripled sensitivity of SGA detection is at the cost of the specificity. The
authors showed that for every additional SGA infant who was correctly identified by universal
ultrasonography, there were two additional false positive results. In addition to the fact that only
30% of SGA fetuses are truly growth restricted, even correct detection of SGA may potentially
lead to unnecessary intervention. Moreover, in Sovio et al.’s study, uterine artery Doppler and
UA Doppler did not predict perinatal parameters in SGA infants. This is consistent with what
Oros et al. (2011) have suggested: that UA PI is commonly found to be normal in late gestations
fetuses. In our cohort, only 5/14 IUGR fetuses had their highest UA PI above the 95th percentile
or had absent or reversed end diastolic flow. Five out of 26 normal fetuses also had UA PI
above the 95th percentile at some point in late gestation, which is consistent with the high false-
positive rate of UA PI shown by the DIGITAT study. As a result, more frequent monitoring
with the current screening method in late pregnancies, which largely relies on fetal biometry and
UA Doppler, may not provide additional benefit. Although emerging evidence suggests that
100
assessment of CPR could help identify a fetus at risk for neonatal complications, especially in
near term SGAs, CPR is currently measured infrequently in low-risk pregnancies (Flood et al.,
2014). Although CPR is thought to be more sensitive than UA PI, we only observed an
abnormal CPR (below 5th percentile) in seven out of 14 IUGR fetuses. In keeping with Oros et
al. (2011), who demonstrated that CPR values worsen significantly from 37 weeks until
delivery, we also observed worsened CPR with gestation in half of the IUGR fetuses. However,
the other half of the IUGR fetuses appeared to have improved CPR in later gestation. We would
suggest that the normalization of CPR should not be regarded as evidence of the improvement
of placental function; rather it is due to the diminished flow redistribution in chronic hypoxia as
shown in animal studies (Richardson & Bocking, 1998). This finding provides the rationale to
use the lowest CPR as one of the criteria to identify late-onset IUGR, which also implies that the
accuracy of the detection of brain-sparing would be improved from serial measurements in late
pregnancy. However, it would pose substantial resource implications.
Our ROC analysis suggests that the presence of increased SVC flow by MRI appears to
be a very reliable indicator of IUGR. However, in five IUGR fetuses that had normal flow
distributions measured by both MRI and normal Dopplers, we found reduced SaO2 and DO2 by
MRI, confirming a hemodynamic basis for growth restriction. This illustrates how fetal
oximetry could improve the detection of IUGR. We hypothesize that in these fetuses, fetal VO2
was matched to DO2 through chronic adaptation to hypoxia through slowing of growth. This
switch from acute to chronic adaptation has previously been demonstrated in fetal lambs and
may explain why CPR was noted to improve in half of the IUGR fetuses in our study (Poudel et
al., 2015; Rurak et al., 1990). MRI may therefore be capable of detecting important placental
insufficiency that might otherwise go undetected.
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5.2 Neurodevelopment in late-onset IUGR and further thoughts We acknowledge that the small sample size in this study prevents us from making any
conclusive statements from our brain and neurodevelopmental findings. However, our
preliminary findings would suggest that IUGR newborns have smaller brain size and reduced
white matter and basal ganglia fractional anisotropy. Across the two groups, white matter and
basal ganglia FA were positively correlated with gestational age while ADC was negatively
correlated with gestational age. These assocaitions were expected. ADC is a measure of the
diffusion rate of water molecules in a specific tissue. As the brain matures, newly formed
microstructures will cause water diffusion to slow down, causing ADC to decrease with age
(Counsell et al., 2006). On the other hand, FA describes the degree of anisotropy of a diffusion
process (Basser & Pierpaoli, 1996). An FA value equal to zero indicates unrestricted or random
diffusion, whereas an FA value close to one means that the diffusion occurs unidirectionally in a
three-dimensional axis (Basser & Pierpaoli, 1996). In the white matter, FA was shown to
increase with maturation, which is associated with oligodendrocyte lineage and myelination
(Drobyshevsky et al., 2005). Interestingly, FA is expected to decrease in the cerebral cortex as
the brain matures due to disappearance of the radial glia and increased complex connectivity of
the neurons (McKinstry, 2002; Marin-Padilla, 1992). The different behavior in the deep grey
matter (thalamus) and the cortical grey matter may be explained by the fact that the thalamus
has different microstructures compared to the cortical grey matter. The thalamus is the relaying
center of neuronal signals. It comprises a system of lamellae, which is made up of myelinated
fibers that separate different thalamic subparts (Percheron, 2003). As the brain matures, the fiber
system becomes better developed, and the FA - directional water diffusion pattern, could behave
more similarly to the white matter compared to cortical grey matter. The observed positive
correlation between brain maturation with thalamus FA was also described by Nagasunder et al.
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(2011). Therefore, the observed lower FA in the white matter and basal ganglia in IUGR
newborns would indicate less matured development in those brain regions (Figure 27). In
addition, we found significant reductions in gross motor function in the IUGR subjects on early
follow-up, providing evidence of a functional consequence of the brain dysmaturation.
Furthermore, the impact of IUGR on neonatal neurodevelopment could have been
underestimated in our study because 10 of the IUGR fetuses who were probably more severely
affected by IUGR did not undergo brain MRI.
Although several studies reported an altered ratio of brain metabolites in SGA and IUGR
fetuses using MRI (Story et al., 2011; Sanz-Cortes et al., 2015; Sanz-Cortes et al., 2014), these
studies all had relatively small sample sizes and have not established the association between
these changes and the long-term consequences. The NAA:Choline ratio seems to be one of the
common measures in all these studies. While Story et al. (2011) and Sanz-Cortes et al. (2015)
both showed decreased NAA:Choline ratios in SGA fetuses, Simoes et al. (2015) have found
higher ratios of NAA:Choline in SGA infants at one year of age. This controversy could be due
to the inherent technical difficulties associated with fetal MRS. Another possibility is that SGA
infants could have accelerated growth after birth. In a cohort of 3,633, Paulson et al. (2012)
demonstrated that although severe SGA (birth weight < 3rd percentile) infants had poorer
cognitive performance at nine months of age, the difference diminished at two years of age.
Children born with severe SGA performed equally well in standardized cognitive and motor
assessments at preschool or kindergarten age as children born with normal weight. This study is
well designed, and it accounted for many confounding factors that may influence a child’s
development, including: ethnicity, gender, maternal education, and socioeconomic status and
prematurity (Paulson et al., 2012). Although many other longitudinal follow-up studies argue
that IUGR is associated with subtle adverse effect on neurodevelopment, these studies
103
commonly have limitations that would affect the result. For example, many of the studies do not
have a clear definition of IUGR or used UA Doppler as their criteria for growth restriction.
Some studies used parental questionnaires instead of standardized tests to assess children’s
developmental outcome. Meanwhile, other studies reported poor control of possible
confounding factors. As a result, more investigations should be done to clarify the reliability of
the evidence about the suboptimal neurodevelopment in IUGR children.
Since the evidence of brain injury due to in-utero hypoxia in late-onset IUGR fetuses is
not well established and stillbirth is rare in such population (Boers et al., 2010), we would argue
that the brain is fairly well-preserved by brain-sparing effects as shown by our study results and
that low-birth-weight children may developmentally catch up by earlier childhood (Paulson et
al., 2012). Therefore, early delivery of late-onset IUGR fetuses could bring more harm than
benefit. Late premature birth is associated with complications such as respiratory stress, feeding
difficulties, hypothermia, and hyperbilirubinemia (Fuchs & Gyanfi, 2008), and early delivery of
these babies would considerably expand the cost of neonatal care for them, as the prevalence of
late-onset IUGR is about 10% of the population. At the same time when studying the brain in
terms of the long-term effect of IUGR pregnancies, more studies should consider the impact on
other organs, such as the heart and the kidney, which are much more affected by the circulatory
adaptation to hypoxia (Iruretagoyena et al., 2014; Taylor et al., 1997).
5.3 Limitations
5.3.1 Diagnosis of IUGR
Within this study, a composite scoring system was utilized for the diagnosis of IUGR;
this has advantages over the more simplistic diagnostic criteria. However, the absence of an
agreed prenatal or postnatal “gold-standard” for IUGR diagnosis is a limitation of our study, and
104
the IUGR scoring system we devised for this study has not been evaluated. Standard approaches
to diagnosing IUGR include ultrasound-derived fetal weight estimation, fetal Dopplers, and
postnatal anthropometric criteria (Lausman & Kingdom, 2013; Sifianou, 2010). However,
problems exist with each of these approaches. UA Doppler alone is relatively unreliable for
recognizing late-onset IUGR, as growth restriction is frequently encountered without UA
Doppler changes (Oros et al., 2011). Even when prenatal Doppler assessment includes CPR,
which is shown to be the most sensitive Doppler measure of hemodynamic adaptation to late-
onset placental insufficiency, only a proportion of late-onset IUGR fetuses appear to have
abnormal findings (Oros et al., 2011; DeVore, 2015). Fetal weight alone is a poor
discriminator; a large proportion of fetuses with weights below the 10th centile are SGA without
growth restriction, and fetuses with late-onset IUGR may have a birth weight above the 10th
percentile. The potential for late gestation placental disease is implied by the known risk of
stillbirth through a wide range of fetal weights (Sifianou, 2010; Moraitis et al., 2014). While a
decline in fetal growth from a higher initial rate is likely to be a reasonable marker of late-onset
IUGR, a screening strategy employing serial growth measurements could be limited by resource
availabilities. In late gestation, serial measurements are unreliable when the interval between
measurements is less than 2 weeks (Mongelli et al., 1998). Postnatal criteria such as neonatal
anthropometric measures and placental histopathology, cannot be used to assist diagnosis
prospectively when decisions need to be made regarding timing of delivery. However, they
remain valuable for mechanistic studies, although some anthropometric measures such as
neonatal length may be limited due to their poor reproducibility (Sifianou, 2010; Parra-Saavedra
et al., 2014). Our IUGR score combines all of these parameters in an attempt to overcome the
weaknesses of individual components, and the absence of a standardized criteria for IUGR
diagnosis illustrates the need for better tools for more accurate identification of the condition in
105
utero.
5.3.2 Accuracy of MRI technique
Fetal weight estimation by MRI in term infants is known to be more accurate than
conventional ultrasound biometry techniques (Zaretskey, 2003). Phase contrast blood flow
quantification has been proven to be very accurate, with MPA and AAo measurements made in
adult volunteers concordant within ~2% (Lotz et al., 2002). Phase contrast flow quantification in
fetal vessels is challenging because of fetal motion and the small size of the vessels. MOG was
used to achieve adequate resolution as an alternative to conventional ECG gating. The feasibility
and accuracy of fetal PC with MOG has been established in phantoms and a human model (Seed
et al., 2012; Prsa et al., 2014; Jansz et al., 2010). The branch pulmonary arteries are the smallest
vessels we measured by phase contrast. Although all the fetuses were above 30 weeks of
gestation, some IUGR fetuses may have small branch pulmonary arteries because of the small
body size as well as lower pulmonary blood flow (Richardson & Bocking, 1998). The
pulmonary artery size in these fetuses (Ruano et al., 2007) may be very close to the lower limit
of the size (3mm) for established criteria for accuracy in phase contrast technique (Hofman et
al., 1995). In order to validate the measurements, the measured PBF was compared and
correlated with the calculated PBF. The measured PBF is the sum of measured flow in LPA and
RPA, and the calculated PBF is the difference between MPA flow and DA flow. The agreement
between the values obtained by the two methods (R2 = 0.30, P = 0.0006) suggests the
measurement is reasonably reliable (Appendix III).
Fetal motion and vessel size also impact the measurement of blood T2. Due to the small
size of the SVC and aorta, our measurements do not always meet the established spatial
resolution criteria for avoiding partial volume artifacts when performing T2 mapping (Stainsby
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& Wright, 1998). However, the feasibility of fetal MR oximetry based on T2 quantification is
supported by good agreement with conventional blood gases in the vessels of children with
congenital heart disease, as well as in fetal lambs at baseline and during hypoxia (Nield et al.,
2005 et al.; Wedegartner et al., 2010). Our demonstration of the same relationships in SaO2
between different vessels that have been shown in fetal lambs using invasive measurements also
support the validity of fetal MR oximetry. The non-rigid registration motion correction
algorithm we used is also likely to reduce the artefacts resulting from fetal occurring motion
between individual T2 preparation images (Sun et al., 2015).
However, the conversion of T2 to SaO2 used in our study is derived from adult blood
experiments and does not account for potential differences in the magnetic properties of fetal
hemoglobin. The error was demonstrated by the higher fetal CDO2 than DO2 in some of the
IUGR fetuses. Recent work by our collaborators (Portnoy et al., 2015) tested the relationship
between SaO2 and T2 in newborn cord blood under 1.5Tesla. They found the MR relaxation
properties of the cord blood and adult blood were similar, but fetal blood T2 relaxation times
were up to 35% longer. As shown in Appendix IV, the T2 values were similar for fetal and
adult blood when SaO2 is high, and fetal blood appeared to have higher T2 at lower SaO2s.
Therefore, UV, which has the highest SaO2, tends to be more accurately calculated with the
conversion based on adult blood. As a result, the DO2, would be reasonably accurate because it
is calculated based on UV T2. However, the average T2 in the AAo was about 125ms in the
normal group and 92ms in the IUGR group. The current conversion would therefore provide an
over-estimated SaO2, and as a result, CDO2 would also be overestimated.
The relationship between T2 and SaO2 also relies on hematocrit. Currently there is no
reliable non-invasive method for measuring fetal hematocrit; therefore, an estimated hematocrit
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was used (Nicolaides et al., 1988). Although this may be appropriate in the normal fetus,
chronic fetal hypoxia is associated with polycythemia. Higher hemoglobin concentration would
shorten T2 in blood in all vessels and therefore DO2 will be underestimated because UV SaO2
is underestimated (Hermansen, 2001; Baschat et al., 1999). However, as VO2 is primarily
determined by the difference in T2 between UV and DAo, the reduction we observed in fetal
VO2 was unlikely due to polycythemia. Population data suggest that the normal fetal
hemoglobin concentration is maintained within a narrow range (Nicolaides et al., 1988).
Nevertheless, technical limitations relating to the requirement for adequate spatial resolution and
signal-to- noise ratio, while achieving practical scan times, currently make this MRI technique
unsuitable for use in earlier gestations.
Finally, while our method has provided information on fetal cerebral oxygen delivery in
IUGR, it does not provide any information on the delivery of other metabolic substrates
important for brain growth and development. Of these other fuels, perhaps the most important
is likely to be glucose. Charlton and Johengen measured the upper and lower limb arterial
content of glucose and oxygen in fetal lambs, and found that glucose and oxygen levels were
closely related (Charlton & Johengen, 1984). However, while the difference in glucose was
10%, the difference in SaO2 was 29%, raising the possibility that the reductions we found in
CDO2 in fetuses with IUGR might have been more profound than any associated reductions in
fetal cerebral glucose delivery.
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6 Conclusion and Future Directions Our MRI technology incorporating blood flow and oxygen saturation provides a novel
perspective on IUGR fetal cardiovascular physiology that is not accessible by conventional
Doppler ultrasound. It could also provide an additional facet to previously described MRI
techniques for analyzing the morphology of placental disease (Damodaram et al., 2010). The
evaluation of fetal oxygenation, as well as fetal cerebral oxygen delivery and consumption by
MRI, could potentially detect a compromised fetal condition before adaptive flow redistribution
occurs or after the resolution of the redistribution. To fully assess the utility of MRI for
diagnosing occult late-onset IUGR, further investigation with a larger sample size would be
needed. Furthermore, the higher cost and limited availability of MRI will ensure that in the
future, ultrasound is likely to remain the primary modality for detecting and monitoring late-
onset IUGR.
Interest remains in the possibility that some of the neurodevelopmental burden
associated with late-onset IUGR could be averted with a timely delivery. In our study, the
neonatal brain imaging findings were in keeping with subtle impairment of brain growth and
development in keeping with animal models showing delayed myelination and reduced cortical
synaptogenesis. Furthermore, more profound abnormalities could have been present in the 15
subjects that did not undergo a brain MRI. In addition, we showed evidence of a functional
sequela of the abnormal fetal brain development on neurodevelopmental testing. However, both
the brain size discrepancy and deficits in cognitive function appeared to resolve with increasing
time from the in utero insult. This is in keeping with some prior studies suggesting there is
catch-up growth of the brain following IUGR and that the long-term neurodevelopmental
sequela reported in IUGR may result primarily from the poor socio-economic status of IUGR
109
subjects compared with their unaffected peers (De wit et al., 2013; Theodore et al., 2009). It
seems possible that compensatory fetal hemodynamic mechanisms to protect the brain and
postnatal catch up growth are effective mitigators of the impact of IUGR on brain development.
The potential benefits of early delivery from chronic fetal hypoxia therefore need to be weighed
carefully against the potential harms of iatrogenic late premature delivery for late-onset IUGR.
An important first step in addressing this important clinical issue would be more accurate
detection of late-onset IUGR, which could have other important clinical implications including
the potential to reduce stillbirth, as well as morbidity and health care expenditure resulting from
unnecessary late preterm delivery. Our demonstration of the potential utility of this new
approach to fetal monitoring should also galvanize efforts to improve the technique with
modifications to overcome the challenges imposed by imaging the fetus.
6.1 Future directions Although a number of prior studies investigating brain development in IUGR also
showed changes in imaging parameters, the relevance of these changes is still questionable
because of the plasticity of the neonatal brain may enable recovery over time. Further
investigations aimed at establishing associations between fetal cerebral hemodynamics and
neonatal and follow-up brain imaging findings with long-term neurodevelopmental outcomes at
early childhood, school age, and adolescence would be helpful in defining the optimal timing of
delivery in the setting of late-onset IUGR. Long-term follow-up studies should be carefully
designed with clearly defined criteria for IUGR and analyze the impact of confounding factors
on neurodevelopment such as socio-economic status. As implied by our findings and limitations,
the following considerations also warrant further investigation.
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6.1.1 T1 and T2 Calibration for hematocrit and oxygen saturation
Although MR T2 oximetry has been shown to be feasible in fetal studies, the accuracy of
T2 to SaO2 conversion has not been validated. As discussed earlier, a major source of error in
the conversion is the different MR relaxation properties of the fetal hemoglobin and the possible
polycythemia associated with chronic hypoxia in IUGR fetuses. Therefore, our technique might
be improved by defining the true relationships between SaO2, hematocrit, and the MR
parameters of fetal blood. In comparison to T2 relaxation, which is largely determined by SaO2
of the blood, T1 is the longitudinal relaxation time that has been shown to be correlated with
hematocrit and only slightly affected by SaO2 (Liu et al., 2015). A recent study by Liu et al.
(2015) investigated human cord blood T1 and T2 relaxation properties under different
hematocrit and oxygenation and showed that the T1 in cord blood was longer than that of adult
blood. Similar to adult blood (Grgac et al., 2013), the T1 of cord blood was also strongly
associated with hematocrit (1/T1=0.59Hct + 0.3, P < 0.001), and the dependence of T1 on
hematocrit was more important at higher hematocrit (Liu et al., 2015). The investigators
suggested that the higher T1 and T2 observed in cord blood is due to the fact that fetal
hemoglobin has a higher affinity to oxygen. Therefore, under the same oxygenation level, there
would be less free oxygen dissolved in the blood, which result in the different magnetic
properties than the adult blood (Liu et al., 2015). Since blood T1 and T2 both depend on
hematocrit and SaO2 to various degrees, it would be mathematically possible to determine
hematocrit and SaO2 simultaneously when T1 and T2 are determined. Therefore, combining T1
and T2 measurements would improve the accuracy of SaO2 estimation. It would also potentially
provide a non-invasive alternative to cordocentesis for measuring blood oxygen saturation and
hematocrit in different fetal populations (Portnoy et al., 2015).
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6.1.2 Placental function by MRI
Since the majority of late-onset IUGR pregnancies originate from placental pathology,
early diagnosis would guide interventions to improve placental function and pregnancy
outcome. Placental location, maturity, and presence of hemorrhages can be detected by
ultrasound (Grannum et al., 1979). However, as gestation progresses, it becomes more difficult
to perform ultrasound assessments due to the small field of view (Damodaram et al., 2010).
Placental MRI has expanded its role in prenatal diagnosis of placental disease and has provided
additional quantitative and qualitative information to ultrasound assessments. Using MRI,
Damodaram et al. (2010) observed that a thickened and globular shaped placenta is associated
with growth restriction. This finding is in keeping with histological examinations of IUGR
placentas, which often have infarcts or abruptions (Salafia et al., 2006). In addition to
morphological evaluation, MRI also provides important insight into placental functions that are
related to vascularization, oxygenation, and metabolism (Siauve et al., 2015). Dynamic contrast-
enhanced MRI is best in quantifying placental perfusion in animal models (Siauve et al., 2015).
However, the safety of the transplacental passage of the contrast agent has not yet been
established. DWI techniques do not require contrast agents, and could be used to measure
perfusion in the placenta. It has been shown that ADC is significantly decreased in the placentas
of IUGR fetuses (Bonel et al., 2010). Other techniques, including BOLD and MRS, can also be
used to explore placental function (Sorensen et al., 2013; McKelvey & Kay, 2007). BOLD
imaging assessing the response of the placenta to changes in oxygen levels. We hypothesize that
the technique used in our study could also be used to assess placental perfusion and oxygen
exchange once the accuracy of T2 to SaO2 conversion is calibrated based on fetal blood. For
example, a combination of low UV flow (% of CVO) and normal UV T2 could be associated
with an occluded or hyper-coiled umbilical cord, or small placenta, which are abnormalities
112
affecting flow rather than oxygen transfer. Normal UV flow with low UV T2 could be due to
diseases that impair gas exchange, in which oxygen therapy may provide beneficial effect.
Therefore, in future studies, investigation of the association of MRI hemodynamic parameters
with placental histopathological findings will provide an additional tool to diagnose placental
disease in utero.
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Appendices Appendix I. Validation of flow measurements from phase contrast with Metric Optimized
Gating. There were good inter-, intra-observer agreement and reproducibility in phase contrast
flow measurements.
0 100 200 300 400 5000
100
200
300
400
500
Measurement 1 (ml/min/kg)
Mea
sure
men
t 2 (m
l/min
/kg
)
UV
PBF
DAo
DA
SVC
AAo
MPA
R2 = 0.98, P <0.0001Y = 0.97*X + 6.87
Inter-observer validation of MRI flow measurements
100 200 300 400 500
-100
-50
0
50
100
AverageDiff
eren
ce
Bland-Altman of MRI flow measurements
0 100 200 300 4000
100
200
300
400
Intra-observer validation of MRI flow measurements
Measurement 1 (ml/min/kg)
Mea
sure
men
t 2 (m
l/min
/kg
)
UV
PBF
DAo
DA
SVC
AAo
MPA
R2 = 0.97, P < 0.0001Y = 0.95*X + 9.0
100 200 300 400
-100
-50
0
50
100
Average
Diff
eren
ce M
1 - M
2
Bland-Altman of MRI flow measurements
127
0 100 200 300 4000
100
200
300
400
reproducibility of MRI flow measurements
Measurement 1 (ml/min/kg)
Mea
sure
men
t 2 (m
l/min
/kg
)
UV
DAo
DA
SVC
AAo
MPA
R2 = 0.92, P < 0.0001Y = 0.97*X + 1.92
100 200 300 400
-40
-20
0
20
40
60
Average
Diff
eren
ce
Bland-Altman of MRI flow measurements
128
Appendix II. Validation of T2 measurements. There were good inter-, intra-observer
agreement and reproducibility in T2 measurements in different fetal vessels.
0 50 100 150 200 2500
50
100
150
200
250
Inter-observer validation of T2 measurements
Measurement 1 (ms)
Mea
sure
men
t 2 (m
s)
AAo
SVC
DAo
UV
R2 = 0.94, P <0.0001Y = 0.97*X + 2.1
MPA
50 100 150 200 250
-40
-20
0
20
40
60
Average
Diff
eren
ce
Bland-Altman of T2 measurements
0 50 100 150 200 2500
50
100
150
200
250
Measurement 1 (ms)
Mea
sure
men
t 2 (m
s)
MPAUV
AAo
DAo
R2 = 0.98, P < 0.0001Y = 0.97*X + 3.69
SVC
Intra-observer validation of MRI T2 measurements
50 100 150 200 250
-20
-10
0
10
20
Average
Diff
eren
ce M
1- M
2
Bland-Altman of T2 measurements
129
Appendix III. Validation of phase contrast pulmonary blood flow (PBF) measurements.
Each data point compares two measures of PBF in the same subject; one the sum of LPA and
RPA, the other the difference between MPA and DA.
0 100 200 3000
100
200
300
reproducibility of T2 measurements
Measurement 1 (ms)
Mea
sure
men
t 2 (m
s)
MPA
AAO
SVC
UV
R2 = 0.98, P < 0.0001Y = 1.03*X - 4.0
DAO
50 100 150 200 250
-40
-20
0
20
40
Average
Diff
eren
ce M
1- M
2
Bland-Altman of T2 measurements
0 100 200 3000
50
100
150
calulated PBF (MPA-DA) (ml/min/kg)
Mea
sure
d PB
F (L
PA+R
PA) (
ml/m
in/k
g)
R2 = 0.30, P = 0.0006
130
Appendix IV. T2 and oxygen saturation (sO2) correlation. Comparison of T2 versus sO2
between umbilical cord blood and adult blood with Hct = 0.47 (Portnoy et al., 2015).