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Validation of functional Fetal Autonomic Brain Age Score fABAS developed using magnetocardiography for applicability in cardiotocography 1 Hoyer Dirk, 1,2 Pytlik Adelina, 3 Gonçalves Hernâni, 3,4,5 Amorim-Costa Célia, 3,4 Bernardes João, 3,4,5 Ayres-de-Campos Diogo, 1 Witte Otto W, 2 Schleussner Ekkehard, 2 Schneider Uwe 1 Jena University Hospital, Biomagnetic Center, Hans Berger Department of Neurology, 2 Jena University Hospital, Department of Obstetrics, Jena, Germany, 3 CINTESIS, Faculty of Medicine, University of Porto, Porto, Portugal, 4 Department of Obstetrics and Gynecology, Faculty of Medicine, University of Porto; Department of Obstetrics and Gynecology, São João Hospital, Portugal; 5 INEB — Institute of Biomedical Engineering, Portugal Hans Berger Department of Neurology, Biomagnetic Center Dept. of Obstetrics, Div. of Prenatal Diagnostics and Fetal Physiology Study Group ‚Prenatal Monitoring of Fetal Maturation‘ ESGCO 2016, Lancaster

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  • Validation of functional Fetal Autonomic Brain Age Score

    fABAS

    developed using magnetocardiography for applicability in

    cardiotocography

    1Hoyer Dirk, 1,2Pytlik Adelina, 3Gonçalves Hernâni, 3,4,5Amorim-Costa Célia, 3,4Bernardes

    João, 3,4,5Ayres-de-Campos Diogo, 1Witte Otto W, 2Schleussner Ekkehard, 2Schneider Uwe

    1 Jena University Hospital, Biomagnetic Center, Hans Berger Department of Neurology,

    2 Jena University Hospital, Department of Obstetrics, Jena, Germany,

    3 CINTESIS, Faculty of Medicine, University of Porto, Porto, Portugal,

    4 Department of Obstetrics and Gynecology, Faculty of Medicine, University of Porto;

    Department of Obstetrics and Gynecology, São João Hospital, Portugal;

    5 INEB — Institute of Biomedical Engineering, Portugal

    Hans Berger Department of Neurology, Biomagnetic Center

    Dept. of Obstetrics, Div. of Prenatal Diagnostics and Fetal Physiology

    Study Group ‚Prenatal Monitoring of Fetal Maturation‘

    ESGCO 2016, Lancaster

  • Autonomic Nervous System

    prenatal birth postnatal

    Assessment of autonomic nervous function

    heart rate patterns !

    Development of autonomic nervous system and control function

    prenatal influences

    - Stress

    - Physical

    - Psychosocial

    - Nutrition

    - Illness

    - Drugs

    time

    2

  • Formation of fetal behavioural states and heart rate patterns

    Pillai and James

    Obstet Gynecol 1990

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    2F

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    Rate

    (bpm

    )Time (min)

    1F quiet sleep (HRP A)

    2F active sleep (HRP B)

    4F active awakeness (HRP D)

    Nijhuis et al. 1982:

    Fetal behavioural states classification based on body

    movements, eye movements, heart rate patterns,

    >32 weeks gestational age

    3

  • HRV Parameter Calculation Interpretation

    Fluctuation amplitude amplitude 20-95 inter-quantile distance of

    detrended NN interval series

    Fluctuation range of heart beat intervals

    above an approximated baseline

    Complexity gMSE(3) Generalized Mutual Information at

    coarse graining level 3 of NN series

    Complexity of sympatho-vagal modulation

    Pattern formation skewness Skewness of NN interval series Asymmetry, decline of deceleration and

    formation of acceleration patterns

    pNN5

    Percentage of differences between

    adjacent NN intervals > 5 ms

    Formation of vagal modulations

    VLF/LF Ratio between VLF (0.02-0.08 Hz)

    and LF (0.08-0.2 Hz) power

    Baseline fluctuation in relation to

    sympatho-vagal modulations 4

    Fundamental of functional fetal Autonomic Brain Age Score fABAS:

    Universal indices of evolution and development in nature

    • Increasing pattern amplitude

    • Increasing complexity

    • Pattern formation Hoyer et al. PlosONE 2013

  • Autonomic Brain Age Score versus chronological age (MCG recordings)

    5

    fABAS:

    fetal Autonomic Brain Age Score

    30 min recordings

    indetermined state dynamics

    10 min sections

    □ active sleep (2F, HRP B)

    ○ quiet sleep (1F, HRP A)

    WGA: Week Gestational Age

    fABAS (HRV indices that are related to universal developmental indices)

    are associated with functional fetal maturation age Hoyer et al. PlosONE 2013

  • Functional fetal autonomic brain age score (fABAS)

    IUGR ● versus normal ○

    Active sleep (2F), 10 min sections

    from 30 min recordings identified

    Jena data base, Hoyer et al. 2013

    State distribution normal

    HRP A HRP B (2F) HRP D

    113 286 29

    26.4 % 66.8 % 6.8 %

    State distribution IUGR

    HRP A HRP B (2F) HRP D

    4 11 5

    29 % 55 % 25 %

    IntraUterine Growth Restriction – fetal HRV - state depended

    IUGR: sonographically estimated weight

  • Undetermined state,

    5 min recordings

    Bochum data base, Hoyer et al. 2015

    Active sleep (2F), 10 min sections

    from 30 min recordings identified

    Jena data base, Hoyer et al. 2013

    IntraUterine Growth Restriction – fetal HRV – vs. State indifferent 5 min recordings

    Functional fetal autonomic brain age score (fABAS)

    IUGR ● versus normal ○ Validation study, state unclear

    7

    4F ?

  • Problems for clinical application

    Appearance of both behavioural states requires recordings over up to 1 hour and

    longer (FIGO recommendation 60 min )

    - In shorter investigations valuable diagnostics information might be lost

    Recording technology:

    - Magnetocardiography (e.g. 1 kHz sampling rate)

    - precise RR intervals, low artifact rate, reliable, high quality, but expensive

    - Abdominal Electrocardiography (e.g. 1 kHz sampling rate)

    - precise RR intervals, high artifact rate, applications not always reliable,

    limitations due to physiological conduction/isolation conditions

    - Cardiotocography (CTG, ultrasound based)

    - Individual heart beats are not detected, correlation based heart rate (from

    1.2 sec. segments), 5/2 ms resampling/interpolation, recordings not

    continiuously reliable.

  • Objective

    Validation of functional Fetal Autonomic Brain Age Score fABAS

    developed using magnetocardiography (MCG)

    for applicability in cardiotocography (CTG)

  • Material and Methods

    Jena Fetal Monitoring Data Base:

    - 390 MCG recordings over 30 min sampled at 1024 Hz (normal fetuses)

    - Investigation of NN interval series and their time series resampled at 4 Hz

    - Only normal beat intervals (NN) were considered,

  • Learn set Validation (test) set

    SE R2 SE R2

    30min MCGNN 2.68 0.498 MCGres 2.724 0.481

    MCGres 2.647 0.510 CTG 3.719 0.345

    CTG 3.587 0.391 MCGres 2.724 0.481

    Results

    Standard error (SE) and coefficient of determinism (R2) of

    fitted models (learn sets) and the application of this models to test sets

    MCGNN MCGres : Resampling of MCG does not remove relevant information (? ANS controlled modulation maintained ? )

    MCGres CTG : Relevant information is lacking in CTG (? recording quality + lacking individual beat detection ? )

    CTG MCGres : CTG fitted models effect higher goodness in MCGres application (? wide spread dispersion around “correct mean model” in CTG group ? )

  • Standard error (SE) and coefficient of determinism (R2) of

    fitted models (learn sets) and the application of this models to test sets

    Similar relationships in all data sets:

    MCGNN MCGres : Resampling of MCG does not remove relevant information

    MCGres CTG : Relevant information is lacking in CTG

    CTG MCGres : CTG fitted models effect higher goodness in MCGres application

    Learn set Validation (test) set

    SE R2 SE R2

    30min MCGNN 2.68 0.498 MCGres 2.724 0.481

    MCGres 2.647 0.510 CTG 3.719 0.345

    CTG 3.587 0.391 MCGres 2.724 0.481

    1F MCGNN 2.739 0.498 MCGres 2.742 0.497

    MCGres 2.722 0.504 CTG 3.891 0.294

    CTG 3.671 0.368 MCGres 2.721 0.505

    2F MCGNN 2.929 0.395 MCGres 2.966 0.380

    MCGres 2.928 0.395 CTG 3.902 0.257

    CTG 3.766 0.308 MCGres 3.026 0.354

  • Discussion, Conclusion

    - Despite precision loss compared to MCG, CTG recordings provide a valuable

    part of information of the fetal functional autonomic maturation age.

    - The reduced goodness of functional maturation age assessment in the CTG is

    mainly caused by higher random disturbances and less precise instantaneous

    heart rate estimation underlying the heart rate time series at 4 Hz resampling.

    - Precise heart beat detection is necessary for a sufficient assessment of the

    individual fetal functional brain maturation age (autonomic nervous system).

    - fABAS was confirmed as being an appropriate candidate for standardized

    assessment of functional brain developmental age and developmental

    disturbances across different recording techniques.

  • Running Project and Call for Collaboration

    „Development of a clinic suitable marker of fetal autonomic maturation“ (fABAS)

    German Research Foundation (DFG, 2018-2018) with international collaborations

    - Data sets of MCG, ECG, CTG of normal fetal maturation

    - Consideration of environmental/maternal physiological influences

    - Assessment of developmental disturbances (MCG, ECG, CTG data sets)

    - Standards and calibration links across different recording techniques

    - Launch a subsequent extended multi-center study on fetal maturation disturbances

    by 2018

  • Acknowledgements

    Team and Collaborators of „Study Group ‚Prenatal Monitoring of Fetal Maturation‘ Hans Berger Department of Neurology, Biomagnetic Center, Jena University Hospital

    Dept. of Obstetrics, Div. of Prenatal Diagnostics and Fetal Physiology, Jena University Hospital

    Samuel Nowack, Florian Tetschke, Jana Ziegler, Anja Rudolph, Ulrike Wallwitz, Liviu Moraru, Isabelle

    Kynass, Franziska Bode, Martin Bogdanski, Eva-Maria Kowalski, Esther Heinicke. Susan Jaekel,

    Franziska Jaenicke, Angelika Stacke, Carolin Michael, Janine Tegtmeier, Kathrin Kumm, Adelina Pytlik,

    Sophia Leibl, Alexander Schmid, Stefan Claus, Ekkehard Schleussner, Uwe Schneider, Dirk Hoyer

    15

    Funding

    DH, US: German Research Foundation: „Development of a clinic suitable marker of

    fetal autonomic maturation“ (DFG: Ho 1634/15-12, Schn 775/7-1),

    Hernâni Gonçalves: post-doctoral grant (SFRH/BPD/69671/2010), Portugal.

    Collaborating Partners

    Teams in Porto

    Peter van Leeuwen, Bochum