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A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning

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Abstract

Patients with repaired Tetralogy of Fallot commonly suffer from chronic pulmonary valve regurgitations and extremely dilated right ventricle (RV). To reduce risk factors, new pulmonary valves must be re-implanted. However, establishing the best timing for re-intervention is a clinical challenge because of the large variability in RV shape and in pathology evolution. This study aims at quantifying the regional impacts of growth and regurgitations upon the end-diastolic RV anatomy. The ultimate goal is to determine, among clinical variables, predictors for the shape in order to build a statistical model that predicts RV remodelling. The proposed approach relies on aforward model based on currents and LDDMM algorithm to estimate an unbiased template of 18 patients and the deformations towards each individual shape. Cross-sectional multivariate analyses are carried out to assess the effects of body surface area, tricuspid and transpulmonary valve regurgitations upon the RV shape. The statistically significant deformation modes were found clinically relevant. Canonical correlation analysis yielded a generative model that was successfully tested on two new patients.

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Author information

Authors and Affiliations

  1. Asclepios Project, INRIA-Méditerranée, Sophia Antipolis, France

    Tommaso Mansi, Stanley Durrleman, Maxime Sermesant, Hervé Delingette, Xavier Pennec & Nicholas Ayache

  2. Neuroimaging of Epilepsy Laboratory, McGill University, Montreal Neurological Institute, Quebec, Canada

    Boris Bernhardt

  3. Siemens AG, CT SE 5 SCR2, Erlangen, Germany & Chair of Pattern Recognition, University of Erlangen-Nuremberg, Erlangen, Germany

    Ingmar Voigt

  4. UCL Institute of Child Health & Great Ormond Street Hospital for Children, London, United Kingdom

    Philipp Lurz & Andrew M. Taylor

  5. Service de Cardiologie Pédiatrique, Hôpital Necker-Enfants Malades, Paris, France

    Julie Blanc & Younes Boudjemline

Authors
  1. Tommaso Mansi

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  2. Stanley Durrleman

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  3. Boris Bernhardt

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  4. Maxime Sermesant

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  5. Hervé Delingette

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  6. Ingmar Voigt

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  7. Philipp Lurz

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  8. Andrew M. Taylor

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  9. Julie Blanc

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  10. Younes Boudjemline

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  11. Xavier Pennec

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  12. Nicholas Ayache

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Editor information

Editors and Affiliations

  1. Institute of Biomedical Engineering, Imperial College London, London, UK

    Guang-Zhong Yang

  2. Centre for Medical Image Computing, University College London, London, UK

    David Hawkes

  3. Department of Computing, Imperial College London, London, UK

    Daniel Rueckert

  4. Institute of Biomedical Engineering, University of Oxford, Oxford, UK

    Alison Noble

  5. School of Computer Science, University of Manchester, Manchester, UK

    Chris Taylor

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© 2009 Springer-Verlag Berlin Heidelberg

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Mansi, T.et al. (2009). A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning. In: Yang, GZ., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. MICCAI 2009. Lecture Notes in Computer Science, vol 5761. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04268-3_27

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