Identification of capillary rarefaction and resultant prognostication in cardiac allograft patients using coronary wave intensity analysis
Authors: Broyd C.J. PhD1,3, Hernández-Pérez F.2, Segovia J.2, Echavarría-Pinto M PhD.1, Quirós-
Carretero A. PhD1, Salas C.2, Gonzalo N. PhD1, Jiménez-Quevedo P.1, Nombela L.1, Salinas P.1, Núñez-
Gil I.1, Del Trigo M.1., Alonso-Pulpón L.2, Fernández-Ortiz A.1, Macaya C.1., Parker K. PhD3, Hughes A.
PhD4, Mayet J. PhD3, Davies J. PhD3, Escaned J. PhD1.
1. Hospital Clínico San Carlos, Madrid
2. Hospital Universitario Puerta de Hierro, Madrid
3. Imperial College London
4. University College London
Author for correspondence:
Dr Javier Escaned
Department of Cardiology
Hospital Clinico San Carlos
Prof Martin Lagos, S/N
Madrid
Abstract word count:
Word count:
References: 24
Figures: 4
Tables: 1
Running title: Capillary density and CAV prognosis with WIA
Abstract
Introduction: Within cardiac allograft recipients, capillary rarefaction appears to reflect one of the
earliest structural changes of allograft vasculopathy(CAV). Measuring such rarefaction using
coronary flow reserve or intracoronary resistance measurements is hampered because of their
relatively non-specific interrogation of the microcirculatory domain. We investigated the potential of
wave intensity analysis (WIA) to document capillary rarefaction and ultimately for predicting CAV in
a group of transplant patients.
Methods: 44 allograft patients with unobstructed coronary arteries and normal LV function
successfully underwent combined LAD pressure and flow measurements at rest and with
intracoronary adenosine. CFR, HMR, IHDVPS, Pzf and WIA were calculated. In a subgroup of 15
patients, simultaneous right ventricular biopsies were obtained and analysed for capillary density. All
patients were followed up with 1-3 yearly screening angiography.
Results: A statistically significant relationship with capillary density was noted with CFR (r=0.52,
p=0.048) and the backward decompression wave (BDW) (r=-0.65, p<0.01), only the latter of which
was maintained with multiple regression analysis (β=-0.53, p=0.02). Over a mean follow-up of
9.3±5.2 years, the BDW was able to predict outcome in terms of CAV-events (p=0.04) as well as the
development (p=0.01), severity (p=0.04) and rate (p=0.09) of angiographic CAV. Similar trends with
prognosis were noted with IHDVPS but no other microvascular indices.
Conclusions: Within cardiac transplant patients, WIA is able to quantify the early histological
changes of CAV, namely capillary rarefaction, and can predict clinical and angiographic outcomes.
This proof-of-concept for WIA also lends weight to its used in the assessment of other disease
processes in which capillary rarefaction is involved.
Key words: vasculopathy, coronary artery, physiology, microcirculation, cardiac transplant
AbbreviationsAOI – Arteriolar Obliteration Index
BDW – Backward Decompression Wave
BMR – Basal Microvascular Resistance
CAV – Cardiac Allograft Vasculopathy
CFR – Coronary Flow Reserve
HMR – Hyperemic Microvascular Resistance
IHDVPS – Instantaneous Hyperemic Diastolic Velocity Pressure Slope
iMR – Index of Microcirculatory Resistance
ISHLT – International Society for Heart and Lung Transplantation
IVUS – IntraVascular UltraSound
WIA – Wave Intensity Analysis
Pzf – Zero Flow Pressure
Introduction
Structural remodelling of the coronary microcirculation occurs in a number of conditions resulting in
microcirculatory dysfunction1. A reduction in capillary density (rarefaction) constitutes a specific
form of microcirculatory remodelling resulting in an impairment of coronary haemodynamics and
influencing long-term outcome2,3. Within cardiac allograft recipients, evidence suggests that the
earliest changes of cardiac allograft vasculopathy (CAV) occur as capillary rarefaction4,5 before the
process is clinically appreciable using angiography and IVUS. However, a sound physiology-based
methodology capable of quantifying early-CAV through capillary rarefaction is missing.
Since capillary density is the main determinant of coronary blood capacity6, a physiological technique
capable of quantifying microcirculatory filling during early diastole might provide valuable clues on
the presence of the subtended capillary density. The Backward Decompression Wave (BDW),
measurable through Wave Intensity Analysis (WIA), originates from the microcirculation and is
thought to quantify the re-expansion of the coronary capillary network in early diastole7. As such, it
may give a relatively-specific measure of capillary density and rarefaction uninfluenced by coexisting
arteriolar obliteration whose influence is noted on flow during mid-to-late diastole8. This is
particularly important since such types of structural remodelling may also occur through disease
processes with an independent effect on microcirculatory haemodynamics and outcome8.
To test this hypothesis, and to validate WIA as a diagnostic tool capable of measuring capillary
rarefaction, we analysed coronary pressure and Doppler flow velocity measurements obtained in a
cohort of consecutive of patients that had previously undergone cardiac transplantation in whom
routine angiography had been scheduled. The study had two parts: firstly, a comparison of WIA and
other physiological indices with capillary density estimated by histomorphometric-examination of
simultaneously-obtained endomyocardial biopsies. Secondly, an assessment of the relationship
between WIA and other physiological indices with long-term outcomes in patients with cardiac
transplantation.
Methods
Study population
Fifty-two consecutive heart transplantation patients scheduled for routine follow-up cardiac
catheterization and endomyocardial biopsy were included in this study; all transplant patients had
angiographically normal coronary arteries at enrolment. The study was approved by the centre’s
ethics committee, and all participants provided informed consent.
Data acquisition
All patients underwent coronary pressure and flow acquisition and the following indices were
constructed: Coronary Flow Reserve (CFR), Basal Microvascular Resistance (BMR), Hyperemic
Microvascular Resistance (HMR), IHDVPS (Instantaneous Hyperaemic Diastolic Velocity Pressure
Slope), Zero Flow Pressure (Pzf) and WIA. A subgroup of 17 patients underwent a simultaneous
histological examination in addition to the above physiology measurements to measure capillary
density and the arteriolar-obliteration index (AOI); 8 control patients were included for comparison
(for details, see the Methods section in the Supplementary Appendix, available at NEJM.org).
Follow up
The Cardiac Allograft Vasculopathy (CAV) end-point was defined as a pre-determined composite of
all CAV-related events incorporating CAV-related death, re-transplantation and re-vascularisation.
Patients underwent 1-3 yearly clinical and angiographic screening to identify evidence of CAV. Once
identified, it was quantified according to standard ISHLT grading9. IVUS findings were stratified
according to the Stanford classification10.
Statistics
Data analyses were performed by STATA 13.1 for Windows (STATA software, TX, USA). Significant
differences between the study subgroups were determined by Student’s t-test. ISHLT data were
analysed using one-way repeated measures analysis of variance with post-hoc Tukey-Kramer
correction. Linear regression analysis was performed to assess univariate relationships between
continuous variables. Multiple linear regression analysis was used to perform statistical adjustments
to the microcirculatory features for capillary density, physiological measures and prognostic
outcome. Survival free of CAV was analysed with the Kaplan-Meier method, using the log rank test
for comparison between groups. A p value of <0.05 was considered statistically significant.
Physiological analysis was performed by an investigator blinded to the clinical and histological
outcome. For convenience, when displayed in bar-charts the backward decompression wave is
shown as positive values. Similarly, when discussing relative wave-intensity sizes, backward
decompression wave magnitude refers to absolute values (i.e. -1 is “less than” -10).
Results
Adequate physiological data was obtained in 44 patients of whom 15 had undergone histological
assessment; these patients are referred to as our study population. Baseline demographics are
demonstrated in Table 1. All patients successfully completed the physiological±histological study
according to the protocol described without complications.
Physiological data
All patients were in sinus rhythm, with a baseline heart rate of 70±17 bpm and normal left
ventricular function. Table S1 in the Supplementary Appendix shows the mean values of the indices
of microcirculatory function measured. No statistically significant influence of hypertension, diabetes
mellitus, or dyslipidaemia were noted on any of the indices of microcirculatory function.
Histological data
An average of 4 biopsies were obtained in each patient. Arteriolar density was similar in transplant
biopsies (2.00±1.22 arterioles per 1 mm2) and control subjects (2.50±0.75 arterioles per 1 mm2,
p=0.3). Capillary density was significantly lower (623±179 vs 1101±322 capillaries per 1 mm2, p<0.01)
in transplant biopsies than in control subjects (Figure S1 in the Supplementary Appendix).
Univariate regression analysis comparing the physiological indices with capillary density was
performed. The strongest relationship was between capillary density and the backward
decompression wave (r=-0.65, p<0.01). A statistically significant relationship with capillary density
was noted with CFR (r=0.52, p=0.048) and a trend towards significance with IHDVPS (r=0.51,
p=0.055) and HMR (r=-0.47, p=0.08) was noted but none with BMR (r=0.36, p=0.2) or Pzf (r=0.13,
p=0.7). (Figure 1). Only the backward decompression wave remained significant on multiple
regression analysis (β=-0.53, p=0.02).
Mean AOI was 77.1 ± 6.2%. A significant relationship was noted between arteriolar obliteration
index and IHDVPS (r=-0.59, p=0.02), but not with the backward decompression wave (r=0.25, p=0.3)
or any other indices of microvascular function.
Follow-up
Two patients were lost to follow-up. Of the remaining 42, mean follow up was 9.3±5.2 years. During
this period there were 12 composite events (CAV-death 5, re-transplantation 4, re-vascularisation 3).
The backward decompression wave was significantly lower in patients suffering an event than those
event-free (-4.5±2.5 vs -7.1±3.9 x103 Wm-2s-1, p=0.04). A similar trend was noted with IHDVPS
(1.2±0.8 vs 1.8±1.2 cm/s/mmHg, p =0.09). No relationship was noted with the other markers of
microvascular function or other waves in the wave-intensity profile (Figure 2).
21 patients ultimately developed angiographic-CAV. Those who did so had a lower IHDVPS value
(1.2±0.8 vs 2.1±1.2 cm/s/mmHg, p=0.01) and a smaller BDW (-4.8±2.6 vs -7.9±4.1 x103 Wm-2s-1,
p=0.01) .
Furthermore, there was a decrease in the backward decompression wave with increasing ISHLT
grade (-7.6±4.0 vs -5.2±2.9 vs -5.6±3.0 vs 4.2±2.3 x103 Wm-2s-1, p=0.07) and IHDVPS (2.1±1.2 vs
1.6±1.0 vs 1.2±0.2 vs 0.9±0.4 cm/s/mmHg, p=0.02) (Figure S2 in the Supplementary Appendix).
Likewise, those who went into to develop the severest disease at IVUS (Stanford IV) had a smaller
BDW at enrolment than those with Stanford III or less (-5.6±6.1 vs -7.9±1.1 Wm -2s-1, p=0.047). No
other relationship between the development of angiographic- or IVUS-CAV and markers of
microcirculatory function were noted.
As there are no standardised normal ranges for wave-intensity in cardiac allograft patients as yet, we
used a cut-off of the 20th percentile of capillary density as a histological poor prognostic marker.
From a linear regression line, the backward decompression wave at this point was calculated as -
5.63x103 Wm-2s-1. Using this cut-off we examined the rate of development of angiographic CAV
disease. Initially, rates were similar; however, there was a divergence over time with higher rates
occurring in those values below the 20th percentile compared to those above it (p=0.09, Figure 3). No
other markers (including IHDVPS, p=0.4) of microvascular function produced an equivalent trend.
To assess for possible confounders, we examined other known predictors for CAV with angiographic
outcomes. Univariate regression also revealed a relationship with recipient diabetes (p=0.04) but not
with donor age (p=0.5), donor sex (p=0.6), recipient cardiac diagnosis (p=0.8), recipient age at
transplantation (p=0.6), surgical ischemic time (p=0.5) or time from index catheterisation (p=0.2).
Multiple regression analysis showed the backward decompression wave (β=0.31, p=0.03) and
IHDVPS (β=-0.35, p=0.01) remained significant but diabetes did not (β=-0.23, p=0.09).
Discussion
The novel findings of this study are:
1. Coronary wave intensity analysis is an intracoronary physiology technique capable of assessing
capillary density in the subtended myocardium
2. Whilst other markers can also provide a measure of capillary density, WIA is the most accurate
tool for this domain
3. In cardiac transplantation patients, the histological evidence of capillary rarefaction is present
before angiographic disease develops which can therefore be identified using wave-intensity
analysis.
4. In turn, this predicts the likelihood of a clinical CAV-event as well as the presence, rate of
development and resultant severity of angiographic CAV (Figure 4).
Wave intensity analysis and capillary density
Cardiac capillary rarefaction is an important pathogenic process in a number of cardiovascular and
systemic diseases but obtaining this information in vivo remains difficult. We have shown that the
backward decompression wave is an adequate measure of capillary density and is able to identify
capillary rarefaction. Whilst both CFR and IHDVPS are also both predictive of capillary density2,8, the
backward decompression wave is more accurate than any other conventional pressure/flow-derived
measures of microvascular function.
Coronary wave intensity analysis was first performed 10 years ago in humans and since then has
been used in a number of physiology studies to predict outcome11 or delineate mechanistic
information12–14. Six waves are identified within each cardiac cycle and each have been ascribed to
particular temporal cardiac processes7. Despite the wealth of clinical insight WIA has provided, until
now this ascription has been based largely on theoretical concepts.
The most clinically relevant wave is the backward decompression wave. This wave is proposed to
originate from the diastolic re-expansion of the intra-myocardial vessels that have been compressed
during systole, akin to a sponge being squeezed then immersed in water before being released.
Work in normal coronary arteries7 and in severe aortic stenosis13 confirmed an appropriate
relationship between the forward compression wave (the ‘squeezing’ force) and the backward
decompression wave. Furthermore, disruption of this relaxation, such as with left ventricular
hypertrophy, causes an alteration in this relationship7. However, these findings only provide a
relatively indirect support for the origin of this wave.
In this series of patients, who are subject to no other obvious influencers of wave intensity, we have
shown that the backward decompression wave relates very closely with the density of capillaries
permeating the myocardium. This therefore provides the first non-physiology-based direct evidence
to support the theoretical concepts of this coronary wave.
Wave intensity analysis to predict cardiac allograft vasculopathy
Cardiac allograft vasculopathy continues to limit the long-term success of cardiac transplantation. It
is a fibro-proliferative disorder that begins within the microcirculation and ultimately progresses to
cause accelerated coronary artery disease with diffuse and circumferential intimal lesions that
progress to occlude coronary blood flow. Given the asensory nature of transplanted-hearts, CAV
currently necessitates frequent angiographic screening15 which incurs significant clinical implications
as well as cost. However, its rate of development remains unpredictable. Accurate diagnosis of pre-
clinical CAV would allow more accurate risk stratification, prognostication, appropriate aggressive
therapy and improve cost-effectiveness and as such is being sought through a number of modalities.
Although distinct from atherosclerotic heart-disease, CAV shares some features with this
pathological process including involvement of the microcirculation16,17. Biopsy-based studies have
identified structural changes that occur within the microcirculation within the first 1-3 months after
transplantation reflecting the earliest stages of CAV4,18 of which capillary rarefaction is a key process5.
Using histological analysis, we have confirmed here that capillary (but not arteriolar) density is
reduced in cardiac transplant patients compared to controls. Given this finding, we used our novel
physiological marker of rarefaction to predict the development, rate of progression and outcome of
CAV.
After a mean follow-up period of nearly 10 years 50% of patients had developed angiographic
evidence of CAV which is consistent with current contemporary practice19. This feature could be
predicted from both the backward decompression wave and IHDVPS but not through any other
markers of microvascular function. Wave-intensity was also able to anticipate its rate of progression
and resultant IVUS severity. Therefore, it appears that the degree of microcirculatory involvement
demonstrated by WIA reflects both the angiographic severity and rate of occurrence of CAV.
We defined a composite endpoint of adverse CAV-related events which included CAV-death, re-
transplantation and revascularisation. Of our pre-defined markers of microvascular function, only
the backward decompression wave was able to identify patients at risk of these events. Potential
future clinical use of this information is suggested in the Supplementary Appendix, available at
NEJM.org.
Other markers of microvascular function
Several other intracoronary physiology tools can be used in vivo to investigate the microcirculation
including CFR, HMR, the index of Microcirculatory Resistance (iMR), IHDVPS and zero-flow pressure
(Pzf). Some of these markers have already been used to provide clinical and physiological insights
into cardiac allograft patients8,20,21. Our analysis incorporated all contemporary non-thermodilutonal
markers of microvascular function but none performed as well as wave-intensity analysis in
identifying histological and prognostic information in this group of patients.
IHDVPS is an alternative way to integrate pressure and flow responses and provides a measure of
conductance. Previous work has shown that this marker correlates with capillary density8 and again
we found a trend here which may have reached significance with a larger patient population.
IHDVPS was also capable of providing some useful insights into prognosis particularly in delineating
the resultant ISHLT-grade of disease severity. However, because of its dual influence from both the
capillary and arteriolar domain it does not provide such a dedicated insight into capillary density as
WIA. We speculate that mid-to-late diastole is governed by the combined resistance effect of the
arterioles and capillaries which is therefore appreciable with IHDVPS. However, in early diastole the
dominant influence is the capacitance of the re-expanding capillaries. Despite this, we are
encouraged by the supportive information provided by IHDVPS in this cohort of patients reinforcing
our earlier work in this field8. We would highlight that rarely does a disease process solely affect one
component of the microcirculation and alternate modalities (such as IHDVPS in this cohort) may
provide important complimentary data.
Whilst Pzf is also constructed from pressure-flow loops it appears to provide differing clinical
information. It is influenced markedly by LVEDP22 and following myocardial infarction provides
significant prognostic information23,24. However, unlike IHDVPS it does not provide information on
microcirculatory histology or predictive data in this study.
CFR has been shown to convey prognostic information regarding left ventricular systolic function in
cardiac-transplant patients20 and is correlated with capillary density2. It is not therefore surprising
that this index also provided some predictive information regarding capillary density. However, as
CFR may be influenced by both macro- and micro-vascular disease25 as well as other haemodynamic
parameters26 it does not behave in such a dedicated fashion as the BDW.
To our knowledge there have been no studies linking whole-cycle derived measures of resistance
(BMR or HMR) with outcome in cardiac transplant patients. In this study, we found no significant
correlation with these measures. There was a trend towards a relationship between HMR and
capillary density which may echo the previously documented relationship between iMR and
histology2.
Limitations and disadvantages
Whilst this study produced a vast amount of sophisticated physiological data the number of patients
included was only moderate. However, the quality of data involved was high and the follow-up
rigorous ensuring maximum reliability of these data. Despite this we acknowledge that larger studies
are required before these findings can be extrapolated to the entire population.
Biopsies were obtained from the right ventricular approach but wave-intensity provided information
on the left ventricle (as it was assessed in the LAD). However, animal studies have shown a
reasonable correlation between right and left ventricular capillary densities27,28 when left ventricular
hypertrophy is absent therefore we feel the two measurements are comparable. Additionally, our
biopsy samples were obtained from the septum which we believe would provide a reasonable
measure of the LAD territory.
We were forced to exclude 8 (15%) patient from our analysis due to poor quality pressure and/or
flow signals. However, with more modern techniques and equipment, and increasing experience we
envisage this percentage could be markedly reduced if used clinically. There was nothing to suggest
those patients excluded were in any way different from our study cohort.
The majority of the index data for this study was gathered prior to the introduction of the combined
Doppler- and pressure-sensor tipped coronary wires that are used for conventional wave-intensity
analysis. Therefore, the pressure signal was obtained from the tip of the catheter rather than at the
same location as the flow-wire. However, we anticipate these waveforms to be identical in the
absence of any epicardial disease – this remains the fundamental basis behind physiological
coronary stenosis assessment in widespread clinical use.
Conclusions
Wave intensity analysis is an excellent tool for assessing capillary rarefaction and provides a focused
insight into the capillary domain of the microcirculation. In cardiac transplant patients, it can identify
the earliest changes of CAV and is able to predict the rate and severity of disease progression. It
therefore confers prognostic outcome data regarding CAV-endpoints. Wave-intensity analysis has a
strong correlate with histological data providing strength to previous theoretical suggestions
regarding the origin of the backward decompression wave.
Funding Sources
Dr Broyd was supported by a grant from the Fundación Interhospitalaria para la Investigación
Cardiovascular (FIC). Dr JE Davies (FS/05/006) is a British Heart Foundation fellow.
Disclosures
None to report.
Tables
Table 1. Baseline characteristic for donor and recipients
Donor
Age (years) 29.2 ± 9.8
Male (%) 36 (82%)
Cause of death
Intracranial haemorrhage (%) 13 (30%)
Other (%) 31 (70%)
Recipient
Age at assessment (years) 54.1 ± 12.7
Age at transplantation (years) 49.2 ± 13.3
Time from transplantation to assessment (months) 59.6 ± 55.0
Reason for transplantation
Dilated cardiomyopathy 22 (50%)
Ischemic cardiomyopathy 12 (27%)
Restrictive cardiomyopathy 5 (11%)
Hypertrophic cardiomyopathy 1 (2.3%)
Valvular heart disease 2 (4.5%)
Congenital heart disease 1 (2.3%)
Re-transplantation 1 (2.3%)
Hypertension 26 (59%)
Hypercholesterolaemia 34 (77%)
Diabetes 14 (32%)
Smoked since transplantation 1 (2.3%)
Table 1. Baseline characteristic for donor and recipients
Figures
Figure 1. Linear regression analysis of 4 indices of microcirculatory function and capillary density
Figure 2. Comparison of the values of 4 indices of microcirculatory function in patients without
(shaded boxes) and with (white boxes) cardiac-allograft vasculopathy driven events during follow-up
(FU).
Figure 3. Kaplin-Meier curve demonstrating survival free from cardiac allograft vasculopathy
(diagnosed angiographically) according to the backward decompression wave.
Figure 4. Schematic representation of the process of cardiac allograft vasculopathy and the ability of
coronary WIA to predict rate and severity of angiographic and clinical outcomes
Figure 1. Linear regression analysis of 4 indices of microcirculatory function and capillary density
The strongest relationship was found between the backward decompression wave and capillary density. Whilst a trend towards significance was noted with
HMR and IHDVPS and a significant relationship with observed with CFR the BDW was the most predictively strong.
Figure 2. Comparison of the values of 4 indices of microcirculatory function in patients without (shaded boxes) and with (white boxes) cardiac-allograft vasculopathy driven events during follow-up (FU).
CAV-related events (a composite of CAV-related death, re-transplantation and re-vascularisation)
were most accurately predicted with the backward decompression wave and this was the only
physiological tool that reached significance.
Figure 3. Kaplin-Meier curve demonstrating survival free from cardiac allograft vasculopathy (diagnosed angiographically) according to the backward
decompression wave.
The backward decompression wave reflecting the 20th percentile of capillary density was used as a cut-off.
Figure 4. Schematic representation of the process of cardiac allograft vasculopathy and the ability of coronary WIA to predict rate and severity of
angiographic and clinical outcomes
In the first few months following transplantation, more severe capillary rarefection occurs in those patients who ultimately go on to develop
angiographically and clinical severe allograft vasculopathy. This change is quantifiable using wave intensity analysis where the size of the BDW identifies
capillary rarefaction and therefore predicts the rate and severity of angiographic and clinical disease and could guide screening rates.
References
1. Pries AR, Badimon L, Bugiardini R, Camici PG, Dorobantu M, Duncker DJ, Escaned J, Koller A, Piek JJ deWit C. Coronary vascular regulation, remodelling, and collateralization: mechanisms and clinical implications on behalf of the working group on coronary pathophysiology and microcirculation. Eur Hear J
2. Tsagalou EP, Anastasiou-Nana M, Agapitos E, et al. Depressed coronary flow reserve is associated with decreased myocardial capillary density in patients with heart failure due to idiopathic dilated cardiomyopathy. J Am Coll Cardiol 2008;52(17):1391–8.
3. Kaul S, Jayaweera AR. Myocardial capillaries and coronary flow reserve. J. Am. Coll. Cardiol. 2008;52(17):1399–401.
4. Hiemann N., Meyer R, Wellnhofer E, Klimek W., Bocksch W, Hetzer R. Correlation of angiographic and immunohistochemical findings in graft vessel disease after heart transplantation. Transplant Proc [Internet] 2001 [cited 2015 Jun 11];33(1–2):1586–90. Available from: http://www.sciencedirect.com/science/article/pii/S004113450002604X
5. Hiemann NE, Meyer R, Wellnhofer E. Letter by Hiemann et al regarding article, “Assessment of microcirculatory remodeling with intracoronary flow velocity and pressure measurements: validation with endomyocardial sampling in cardiac allografts”. Circulation [Internet] 2010 [cited 2015 Jun 11];122(4):e404; author reply e405. Available from: http://circ.ahajournals.org/content/122/4/e404.full
6. Van Kerckhoven R, van Veghel R, Saxena PR, Schoemaker RG. Pharmacological therapy can increase capillary density in post-infarction remodeled rat hearts. Cardiovasc Res [Internet] 2004;61(3):620–9. Available from: http://cardiovascres.oxfordjournals.org/content/61/3/620.abstract
7. Davies JE, Whinnett ZI, Francis DP, et al. Evidence of a Dominant Backward-Propagating “Suction” Wave Responsible for Diastolic Coronary Filling in Humans, Attenuated in Left Ventricular Hypertrophy. Circulation [Internet] 2006;113(14):1768–78. Available from: http://circ.ahajournals.org/cgi/content/abstract/113/14/1768
8. Escaned J, Flores A, Garcia-Pavia P, et al. Assessment of microcirculatory remodeling with intracoronary flow velocity and pressure measurements: validation with endomyocardial sampling in cardiac allografts. Circulation 2009;120(16):1561–8.
9. Mehra MR, Crespo-Leiro MG, Dipchand A, et al. International Society for Heart and Lung Transplantation working formulation of a standardized nomenclature for cardiac allograft vasculopathy-2010. J Heart Lung Transplant [Internet] 2010 [cited 2015 May 18];29(7):717–27. Available from: http://www.jhltonline.org/article/S1053249810003128/fulltext
10. St Goar FG, Pinto FJ, Alderman EL, et al. Intracoronary ultrasound in cardiac transplant recipients. In vivo evidence of “angiographically silent” intimal thickening. Circulation [Internet] 1992;85(3):979–87. Available from: http://circ.ahajournals.org/content/85/3/979.abstract
11. Silva K De, Guilcher A, Lockie T, et al. CORONARY WAVE INTENSITY: A NOVEL INVASIVE TOOL FOR PREDICTING MYOCARDIAL VIABILITY FOLLOWING ACUTE CORONARY SYNDROMES. J Am Coll Cardiol [Internet] 2012;59(13s1):E421–E421. Available from: http://dx.doi.org/10.1016/S0735-1097(12)60422-7
12. Kyriacou A, Whinnett ZI, Sen S, et al. Improvement in Coronary Blood Flow Velocity With
Acute Biventricular Pacing Is Predominantly Due to an Increase in a Diastolic Backward-Travelling Decompression (Suction) Wave. Circulation [Internet] 2012;126(11):1334–44. Available from: http://circ.ahajournals.org/content/126/11/1334.abstract
13. Davies JE, Sen S, Broyd C, et al. Arterial pulse wave dynamics after percutaneous aortic valve replacement: Fall in coronary diastolic suction with increasing heart rate as a basis for angina symptoms in aortic stenosis. Circulation 2011;124(14):1565–72.
14. Lockie TP, Rolandi MC, Guilcher A, et al. Synergistic adaptations to exercise in the systemic and coronary circulations that underlie the warm-up angina phenomenon. Circulation 2012;126(22):2565–74.
15. Costanzo MR, Dipchand A, Starling R, et al. The International Society of Heart and Lung Transplantation Guidelines for the care of heart transplant recipients. J Hear Lung Transpl 2010;29(8):914–56.
16. Tanaka H, Swanson SJ, Sukhova G, Schoen FJ, Libby P. Early proliferation of medial smooth muscle cells in coronary arteries of rabbit cardiac allografts during immunosuppression with cyclosporine A. Transplant Proc [Internet] 1995 [cited 2015 Jun 8];27(3):2062–5. Available from: http://www.ncbi.nlm.nih.gov/pubmed/7792886
17. Kofoed KF, Czernin J, Johnson J, et al. Effects of Cardiac Allograft Vasculopathy on Myocardial Blood Flow, Vasodilatory Capacity, and Coronary Vasomotion. Circulation [Internet] 1997;95(3):600–6. Available from: http://circ.ahajournals.org/content/95/3/600.abstract
18. Labarrere CA, Nelson DR, Faulk WP. Myocardial fibrin deposits in the first month after transplantation predict subsequent coronary artery disease and graft failure in cardiac allograft recipients. Am J Med 1998;105(3):207–13.
19. Stehlik J, Edwards LB, Kucheryavaya AY, et al. The Registry of the International Society for Heart and Lung Transplantation: twenty-seventh official adult heart transplant report--2010. J Hear Lung Transpl 2010;29(10):1089–103.
20. Weis M, Hartmann A, Olbrich HG, Hor G, Zeiher AM. Prognostic significance of coronary flow reserve on left ventricular ejection fraction in cardiac transplant recipients. Transplantation 1998;65(1):103–8.
21. Fearon WF, Hirohata A, Nakamura M, et al. Discordant changes in epicardial and microvascular coronary physiology after cardiac transplantation: Physiologic Investigation for Transplant Arteriopathy II (PITA II) study. J Hear Lung Transpl 2006;25(7):765–71.
22. Van Herck PL, Carlier SG, Claeys MJ, et al. Coronary microvascular dysfunction after myocardial infarction: increased coronary zero flow pressure both in the infarcted and in the remote myocardium is mainly related to left ventricular filling pressure. Heart [Internet] 2007;93(10):1231–7. Available from: http://heart.bmj.com/content/93/10/1231.abstract
23. Patel N, Petraco R, Dall’Armellina E, et al. Zero-Flow Pressure Measured Immediately After Primary Percutaneous Coronary Intervention for ST-Segment Elevation Myocardial Infarction Provides the Best Invasive Index for Predicting the Extent of Myocardial Infarction at 6 Months: An OxAMI Study (Oxford. JACC Cardiovasc Interv [Internet] 2015 [cited 2016 May 26];8(11):1410–21. Available from: http://www.sciencedirect.com/science/article/pii/S1936879815009917
24. Teunissen PFA, de Waard GA, Hollander MR, et al. Doppler-Derived Intracoronary Physiology Indices Predict the Occurrence of Microvascular Injury and Microvascular Perfusion Deficits After Angiographically Successful Primary Percutaneous Coronary Intervention. Circ Cardiovasc Interv [Internet] 2015;8(3). Available from:
http://circinterventions.ahajournals.org/content/8/3/e001786.abstract
25. Gould KL, Lipscomb K, Hamilton GW. Physiologic basis for assessing critical coronary stenosis: Instantaneous flow response and regional distribution during coronary hyperemia as measures of coronary flow reserve. Am J Cardiol [Internet] 1974;33(1):87–94. Available from: http://www.sciencedirect.com/science/article/pii/0002914974907437
26. de Bruyne B, Bartunek J, Sys SU, Pijls NHJ, Heyndrickx GR, Wijns W. Simultaneous Coronary Pressure and Flow Velocity Measurements in Humans: Feasibility, Reproducibility, and Hemodynamic Dependence of Coronary Flow Velocity Reserve, Hyperemic Flow Versus Pressure Slope Index, and Fractional Flow Reserve. Circulation [Internet] 1996;94(8):1842–9. Available from: http://circ.ahajournals.org/content/94/8/1842.abstract
27. Smith P, Clark DR. Myocardial capillary density and muscle fibre size in rats born and raised at simulated high altitude. Br J Exp Pathol [Internet] 1979 [cited 2015 Jun 18];60(2):225–30. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2041440&tool=pmcentrez&rendertype=abstract
28. Flanagan MF, Aoyagi T, Currier JJ, Colan SP, Fujii AM. Effect of young age on coronary adaptations to left ventricular pressure overload hypertrophy in sheep. J Am Coll Cardiol [Internet] 1994 [cited 2015 Jun 18];24(7):1786–96. Available from: http://www.sciencedirect.com/science/article/pii/0735109794901880