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Computational modelling for congenital heart disease: how far are we from clinical translation?
  1. Giovanni Biglino1,2,
  2. Claudio Capelli2,3,
  3. Jan Bruse2,3,
  4. Giorgia M Bosi2,3,
  5. Andrew M Taylor2,3,
  6. Silvia Schievano2,3
  1. 1Bristol Heart Institute, School of Clinical Sciences, University of Bristol, Bristol, UK
  2. 2Cardiorespiratory Unit, Great Ormond Street Hospital for Children, NHS Foundation Trust, London, UK
  3. 3Institute of Cardiovascular Science, University College London, London, UK
  1. Correspondence to Dr Giovanni Biglino, Bristol Heart Institute, Bristol Royal Infirmary Level 7, Upper Maudlin Street, Bristol BS2 8HW, UK; g.biglino{at}bristol.ac.uk

Abstract

Computational models of congenital heart disease (CHD) have become increasingly sophisticated over the last 20 years. They can provide an insight into complex flow phenomena, allow for testing devices into patient-specific anatomies (pre-CHD or post-CHD repair) and generate predictive data. This has been applied to different CHD scenarios, including patients with single ventricle, tetralogy of Fallot, aortic coarctation and transposition of the great arteries. Patient-specific simulations have been shown to be informative for preprocedural planning in complex cases, allowing for virtual stent deployment. Novel techniques such as statistical shape modelling can further aid in the morphological assessment of CHD, risk stratification of patients and possible identification of new ‘shape biomarkers’. Cardiovascular statistical shape models can provide valuable insights into phenomena such as ventricular growth in tetralogy of Fallot, or morphological aortic arch differences in repaired coarctation. In a constant move towards more realistic simulations, models can also account for multiscale phenomena (eg, thrombus formation) and importantly include measures of uncertainty (ie, CIs around simulation results). While their potential to aid understanding of CHD, surgical/procedural decision-making and personalisation of treatments is undeniable, important elements are still lacking prior to clinical translation of computational models in the field of CHD, that is, large validation studies, cost-effectiveness evaluation and establishing possible improvements in patient outcomes.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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Footnotes

  • Contributors GB, CC, JB, GMB, AMT and SS contributed to drafting the manuscript and approve of its contents.

  • Funding The authors gratefully acknowledge the support of the following funding bodies: British Heart Foundation, Leducq Foundation, the Engineering and Physical Sciences Research Council (EPSRC), and Heart Research UK. This report is independent by the National Institute for Health Research Biomedical Research Centre Funding Scheme. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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