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Longitudinal Analysis Using Personalised 3D Cardiac Models with Population-Based Priors: Application to Paediatric Cardiomyopathies

  • Roch MolleroEmail author
  • Hervé Delingette
  • Manasi Datar
  • Tobias Heimann
  • Jakob A. Hauser
  • Dilveer Panesar
  • Alexander Jones
  • Andrew Taylor
  • Marcus Kelm
  • Titus Kuehne
  • Marcello Chinali
  • Gabriele Rinelli
  • Nicholas Ayache
  • Xavier Pennec
  • Maxime Sermesant
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10434)

Abstract

Personalised 3D modelling of the heart is of increasing interest in order to better characterise pathologies and predict evolution. The personalisation consists in estimating the parameter values of an electromechanical model in order to reproduce the observed cardiac motion. However, the number of parameters in these models can be high and their estimation may not be unique. This variability can be an obstacle to further analyse the estimated parameters and for their clinical interpretation. In this paper we present a method to perform consistent estimations of electromechanical parameters with prior probabilities on the estimated values, which we apply on a large database of 84 different heartbeats. We show that the use of priors reduces considerably the variance in the estimated parameters, enabling better conditioning of the parameters for further analysis of the cardiac function. This is demonstrated by the application to longitudinal data of paediatric cardiomyopathies, where the estimated parameters provide additional information on the pathology and its evolution.

Notes

Ackowledgements

This work has been partially funded by the EU FP7-funded project MD-Paedigree (Grant Agreement 600932) and contributes to the objectives of the ERC advanced grant MedYMA (2011-291080).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Roch Mollero
    • 1
    Email author
  • Hervé Delingette
    • 1
  • Manasi Datar
    • 3
  • Tobias Heimann
    • 3
  • Jakob A. Hauser
    • 2
  • Dilveer Panesar
    • 2
  • Alexander Jones
    • 6
  • Andrew Taylor
    • 2
  • Marcus Kelm
    • 4
  • Titus Kuehne
    • 4
  • Marcello Chinali
    • 5
  • Gabriele Rinelli
    • 5
  • Nicholas Ayache
    • 1
  • Xavier Pennec
    • 1
  • Maxime Sermesant
    • 1
  1. 1.Université Côte d’Azur, Inria, Asclepios TeamSophia AntipolisFrance
  2. 2.UCL Centre for Cardiovascular ImagingLondonUK
  3. 3.Imaging and Computer VisionSiemens Corporate TechnologyErlangenGermany
  4. 4.Deutsches Herzzentrum BerlinBerlinGermany
  5. 5.DMCCP CardiologyOspedale Pediatrico Bambino GesùRomeItaly
  6. 6.Department of PaediatricsUniversity of OxfordOxfordUK

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