Creation and application of virtual patient cohorts of heart models

doi:10.1098/rsta.2019.0558

. 2020 Jun 12;378(2173):20190558.

doi: 10.1098/rsta.2019.0558. Epub 2020 May 25.

Creation and application of virtual patient cohorts of heart models

S A Niederer¹, Y Aboelkassem², C D Cantwell³, C Corrado¹, S Coveney⁴, E M Cherry⁵, T Delhaas⁶, F H Fenton⁵, A V Panfilov^{7

8}, P Pathmanathan⁹, G Plank¹⁰, M Riabiz¹, C H Roney¹, R W Dos Santos¹¹, L Wang¹²

Affiliations

¹ King's College London, London, UK.
² University of California San Diego, La Jolla, CA, USA.
³ Imperial College London, London, UK.
⁴ University of Sheffield, Sheffield, UK.
⁵ Georgia Institute of Technology, Atlanta, GA, USA.
⁶ Maastricht University, Maastricht, the Netherlands.
⁷ Ghent University, Gent, Belgium.
⁸ Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, Russia.
⁹ Center for Devices and Radiological Health, U.S. Food and Administration, Rockville, MD, USA.
¹⁰ Medical University of Graz, Graz, Austria.
¹¹ Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil.
¹² Rochester Institute of Technology, La JollaRochester, NY, USA.

PMID: 32448064
PMCID: PMC7287335
DOI: 10.1098/rsta.2019.0558

Creation and application of virtual patient cohorts of heart models

S A Niederer et al. Philos Trans A Math Phys Eng Sci. 2020.

. 2020 Jun 12;378(2173):20190558.

doi: 10.1098/rsta.2019.0558. Epub 2020 May 25.

Authors

Affiliations

¹ King's College London, London, UK.
² University of California San Diego, La Jolla, CA, USA.
³ Imperial College London, London, UK.
⁴ University of Sheffield, Sheffield, UK.
⁵ Georgia Institute of Technology, Atlanta, GA, USA.
⁶ Maastricht University, Maastricht, the Netherlands.
⁷ Ghent University, Gent, Belgium.
⁸ Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, Russia.
⁹ Center for Devices and Radiological Health, U.S. Food and Administration, Rockville, MD, USA.
¹⁰ Medical University of Graz, Graz, Austria.
¹¹ Universidade Federal de Juiz de Fora, Juiz de Fora, Brazil.
¹² Rochester Institute of Technology, La JollaRochester, NY, USA.

PMID: 32448064
PMCID: PMC7287335
DOI: 10.1098/rsta.2019.0558

Abstract

Patient-specific cardiac models are now being used to guide therapies. The increased use of patient-specific cardiac simulations in clinical care will give rise to the development of virtual cohorts of cardiac models. These cohorts will allow cardiac simulations to capture and quantify inter-patient variability. However, the development of virtual cohorts of cardiac models will require the transformation of cardiac modelling from small numbers of bespoke models to robust and rapid workflows that can create large numbers of models. In this review, we describe the state of the art in virtual cohorts of cardiac models, the process of creating virtual cohorts of cardiac models, and how to generate the individual cohort member models, followed by a discussion of the potential and future applications of virtual cohorts of cardiac models. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Keywords: cardiac; digital twin; simulation; virtual patient cohorts.

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Conflict of interest statement

We declare we have no competing interest.

Figures

**Figure 1.**
Schematic of the strategies for obtaining a virtual cohort, based on biophysical models. (Online version in colour.)

**Figure 2.**
Process of creating a virtual cohort. (a) Defining a template model structure for the members of the cohort, (b) constraining the parameters for the members of the virtual cohort and, (c) validating the models representing specific individual patients and the virtual cohort. (Online version in colour.)

See this image and copyright information in PMC

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References

1. Niederer SA, Lumens J, Trayanova NA. 2019. Computational models in cardiology. Nat. Rev. Cardiol. 16, 100–111. (10.1038/s41569-018-0104-y) - DOI - PMC - PubMed
1. Niederer S, Mitchell L, Smith N, Plank G. 2011. Simulating human cardiac electrophysiology on clinical time-scales. Front. Physiol. 2, 14 (10.3389/fphys.2011.00014) - DOI - PMC - PubMed
1. Augustin CM, Neic A, Liebmann M, Prassl AJ, Niederer SA, Haase G, Plank G. 2016. Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation. J. Comput. Phys. 305, 622–646. (10.1016/j.jcp.2015.10.045) - DOI - PMC - PubMed
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1. Prakosa A. et al. 2018. Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia. Nat. Biomed. Eng. 2, 732–740. (10.1038/s41551-018-0282-2) - DOI - PMC - PubMed

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[1] Niederer SA, Lumens J, Trayanova NA. 2019. Computational models in cardiology. Nat. Rev. Cardiol. 16, 100–111. (10.1038/s41569-018-0104-y) - DOI - PMC - PubMed

[2] Niederer SA, Lumens J, Trayanova NA. 2019. Computational models in cardiology. Nat. Rev. Cardiol. 16, 100–111. (10.1038/s41569-018-0104-y) - DOI - PMC - PubMed

[3] Niederer S, Mitchell L, Smith N, Plank G. 2011. Simulating human cardiac electrophysiology on clinical time-scales. Front. Physiol. 2, 14 (10.3389/fphys.2011.00014) - DOI - PMC - PubMed

[4] Niederer S, Mitchell L, Smith N, Plank G. 2011. Simulating human cardiac electrophysiology on clinical time-scales. Front. Physiol. 2, 14 (10.3389/fphys.2011.00014) - DOI - PMC - PubMed

[5] Augustin CM, Neic A, Liebmann M, Prassl AJ, Niederer SA, Haase G, Plank G. 2016. Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation. J. Comput. Phys. 305, 622–646. (10.1016/j.jcp.2015.10.045) - DOI - PMC - PubMed

[6] Augustin CM, Neic A, Liebmann M, Prassl AJ, Niederer SA, Haase G, Plank G. 2016. Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation. J. Comput. Phys. 305, 622–646. (10.1016/j.jcp.2015.10.045) - DOI - PMC - PubMed

[7] Richards DF. et al. 2013. Towards real-time simulation of cardiac electrophysiology in a human heart at high resolution. Comput. Methods Biomech. Biomed. Eng. 16, 802–805. (10.1080/10255842.2013.795556) - DOI - PubMed

[8] Richards DF. et al. 2013. Towards real-time simulation of cardiac electrophysiology in a human heart at high resolution. Comput. Methods Biomech. Biomed. Eng. 16, 802–805. (10.1080/10255842.2013.795556) - DOI - PubMed

[9] Prakosa A. et al. 2018. Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia. Nat. Biomed. Eng. 2, 732–740. (10.1038/s41551-018-0282-2) - DOI - PMC - PubMed

[10] Prakosa A. et al. 2018. Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia. Nat. Biomed. Eng. 2, 732–740. (10.1038/s41551-018-0282-2) - DOI - PMC - PubMed

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Creation and application of virtual patient cohorts of heart models

Affiliations

Creation and application of virtual patient cohorts of heart models

Authors

Affiliations

Abstract

Conflict of interest statement

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