Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar

Reliable and robust simulation of individual patients using patient-specific models (PSMs) is one of the next frontiers for modeling and simulation (M&S) in healthcare. PSMs, which form the basis of digital twins, can be employed as clinical tools to, for example, assess disease state, predict r...

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Bibliographic Details
Published in:PLoS computational biology Vol. 18; no. 10; p. e1010541
Main Authors: Galappaththige, Suran, Gray, Richard A., Costa, Caroline Mendonca, Niederer, Steven, Pathmanathan, Pras
Format: Journal Article
Language:English
Published: San Francisco Public Library of Science 10.10.2022
Public Library of Science (PLoS)
Subjects:
Biology and Life Sciences
Care and treatment
Computer and Information Sciences
Computer applications
Credibility
Critical path
Customization
Digital twins
Engineering and Technology
Health care
Heart
Medical device industry
Medical electronics
Medical equipment
Medical imaging
Medical technology
Medicine and Health Sciences
Patients
Product safety
Quality control
Research and Analysis Methods
Risk assessment
Simulation
Software quality
Uncertainty
Ventricle
Verification
United States
United States > US
ISSN:1553-7358, 1553-734X, 1553-7358
Online Access:Get full text
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Summary:Reliable and robust simulation of individual patients using patient-specific models (PSMs) is one of the next frontiers for modeling and simulation (M&S) in healthcare. PSMs, which form the basis of digital twins, can be employed as clinical tools to, for example, assess disease state, predict response to therapy, or optimize therapy. They may also be used to construct virtual cohorts of patients, for in silico evaluation of medical product safety and/or performance. Methods and frameworks have recently been proposed for evaluating the credibility of M&S in healthcare applications. However, such efforts have generally been motivated by models of medical devices or generic patient models; how best to evaluate the credibility of PSMs has largely been unexplored. The aim of this paper is to understand and demonstrate the credibility assessment process for PSMs using patient-specific cardiac electrophysiological (EP) modeling as an exemplar. We first review approaches used to generate cardiac PSMs and consider how verification, validation, and uncertainty quantification (VVUQ) apply to cardiac PSMs. Next, we execute two simulation studies using a publicly available virtual cohort of 24 patient-specific ventricular models, the first a multi-patient verification study, the second investigating the impact of uncertainty in personalized and non-personalized inputs in a virtual cohort. We then use the findings from our analyses to identify how important characteristics of PSMs can be considered when assessing credibility with the approach of the ASME V&V40 Standard, accounting for PSM concepts such as inter- and intra-user variability, multi-patient and “every-patient” error estimation, uncertainty quantification in personalized vs non-personalized inputs, clinical validation, and others. The results of this paper will be useful to developers of cardiac and other medical image based PSMs, when assessing PSM credibility.
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The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1010541