Credibility assessment of patient-specific computational modeling using patient-specific cardiac modeling as an exemplar.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
21
04
2022
accepted:
02
09
2022
entrez:
10
10
2022
pubmed:
11
10
2022
medline:
13
10
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36215228
doi: 10.1371/journal.pcbi.1010541
pii: PCOMPBIOL-D-22-00630
pmc: PMC9550052
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1010541Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
PLoS One. 2020 Jun 26;15(6):e0235145
pubmed: 32589679
PLoS One. 2015 Jul 31;10(7):e0134869
pubmed: 26230546
J Physiol. 2012 Jun 1;590(11):2613-28
pubmed: 22473779
Heart Rhythm. 2020 Mar;17(3):408-414
pubmed: 31589989
Med Image Anal. 2018 Jul;47:153-163
pubmed: 29753180
Med Image Anal. 2018 Jul;47:180-190
pubmed: 29753182
Nat Biomed Eng. 2019 Nov;3(11):870-879
pubmed: 31427780
Nat Commun. 2016 May 10;7:11437
pubmed: 27164184
Comput Biol Med. 2020 Aug;123:103895
pubmed: 32741753
Eur Heart J. 2020 Dec 21;41(48):4556-4564
pubmed: 32128588
IEEE Trans Biomed Eng. 2011 Apr;58(4):1066-75
pubmed: 21292591
Europace. 2021 Mar 4;23(23 Suppl 1):i12-i20
pubmed: 33437987
Heart Rhythm. 2020 Nov;17(11):1922-1929
pubmed: 32603781
Comput Methods Biomech Biomed Engin. 2022 Apr;25(5):543-553
pubmed: 34427119
Front Physiol. 2018 Feb 15;9:106
pubmed: 29497385
Comput Biol Med. 2020 Dec;127:104047
pubmed: 33099220
J Cardiovasc Magn Reson. 2019 Feb 28;21(1):14
pubmed: 30813942
Comput Biol Med. 2019 Sep;112:103368
pubmed: 31352217
Ann Biomed Eng. 2016 Jan;44(1):58-70
pubmed: 26424476
Sci Rep. 2018 Oct 19;8(1):15540
pubmed: 30341365
J Biomech. 2011 Jun 3;44(9):1666-72
pubmed: 21497354
Front Physiol. 2020 Nov 19;11:585400
pubmed: 33329034
Front Physiol. 2021 Jul 22;12:693015
pubmed: 34366883
Ann Biomed Eng. 2021 Jan;49(1):233-250
pubmed: 32458222
Ann Biomed Eng. 2020 Jun;48(6):1740-1750
pubmed: 32152800
Phys Med Biol. 2010 Jan 21;55(2):N23-38
pubmed: 20019402
J Math Biol. 1991;29(7):629-51
pubmed: 1940663
PLoS Comput Biol. 2021 Apr 15;17(4):e1008851
pubmed: 33857152
PLoS Comput Biol. 2013;9(3):e1002970
pubmed: 23516352
PLoS Comput Biol. 2016 Aug 05;12(8):e1005060
pubmed: 27494252
Math Biosci. 2016 Nov;281:46-54
pubmed: 27590776
Philos Trans A Math Phys Eng Sci. 2011 Nov 13;369(1954):4331-51
pubmed: 21969679
Circ Res. 2002 May 3;90(8):889-96
pubmed: 11988490
Int J Numer Method Biomed Eng. 2014 May;30(5):525-44
pubmed: 24259465
Ann Biomed Eng. 2021 Apr;49(4):1151-1168
pubmed: 33067688
J Mol Cell Cardiol. 2010 Jan;48(1):112-21
pubmed: 19835882
Am J Physiol Heart Circ Physiol. 2004 Apr;286(4):H1573-89
pubmed: 14656705
Ann Biomed Eng. 2012 Oct;40(10):2243-54
pubmed: 22648575
J Comput Phys. 2017 Oct 1;346:191-211
pubmed: 28819329
Prog Biophys Mol Biol. 2011 Jan;104(1-3):22-48
pubmed: 20553746
Int J Cardiovasc Imaging. 2015 Feb;31(2):359-68
pubmed: 25352244
Europace. 2021 Apr 6;23(4):640-647
pubmed: 33241411
J Cardiovasc Electrophysiol. 2017 Oct;28(10):1158-1166
pubmed: 28670858
IEEE Trans Med Imaging. 2017 Nov;36(11):2261-2275
pubmed: 28742031
Med Image Anal. 2021 Jul;71:102080
pubmed: 33975097
PLoS Comput Biol. 2011 May;7(5):e1002061
pubmed: 21637795
Heart Rhythm. 2019 Oct;16(10):1475-1483
pubmed: 30930329
Med Image Anal. 2012 Jan;16(1):201-15
pubmed: 21920797
Med Image Anal. 2019 Oct;57:197-213
pubmed: 31326854
Front Physiol. 2019 Jun 26;10:721
pubmed: 31297060
Nat Biomed Eng. 2018 Oct;2(10):732-740
pubmed: 30847259
Bull Math Biol. 2003 Sep;65(5):767-93
pubmed: 12909250
Am J Physiol Heart Circ Physiol. 2006 Sep;291(3):H1088-100
pubmed: 16565318
J Cardiovasc Transl Res. 2018 Apr;11(2):80-88
pubmed: 29512059