{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,10]],"date-time":"2026-11-10T18:27:53Z","timestamp":1794335273970,"version":"4.9.0"},"reference-count":49,"publisher":"eLife Sciences Publications, Ltd","license":[{"start":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T00:00:00Z","timestamp":1697587200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T00:00:00Z","timestamp":1697587200000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T00:00:00Z","timestamp":1697587200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01-HL142496"],"award-info":[{"award-number":["R01-HL142496"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["R01HL126802"],"award-info":[{"award-number":["R01HL126802"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Johns Hopkins University","award":["Discovery Award"],"award-info":[{"award-number":["Discovery Award"]}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["T32HL007227"],"award-info":[{"award-number":["T32HL007227"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","award":["L30HL165535"],"award-info":[{"award-number":["L30HL165535"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["elifesciences.org"],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>\n                    Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a genetic cardiac disease that leads to ventricular tachycardia (VT), a life-threatening heart rhythm disorder. Treating ARVC remains challenging due to the complex underlying arrhythmogenic mechanisms, which involve structural and electrophysiological (EP) remodeling. Here, we developed a novel genotype-specific heart digital twin (Geno-DT) approach to investigate the role of pathophysiological remodeling in sustaining VT reentrant circuits and to predict the VT circuits in ARVC patients of different genotypes. This approach integrates the patient\u2019s disease-induced structural remodeling reconstructed from contrast-enhanced magnetic-resonance imaging and genotype-specific cellular EP properties. In our retrospective study of 16 ARVC patients with two genotypes: plakophilin-2 (\n                    <jats:italic>PKP2<\/jats:italic>\n                    ,\n                    <jats:italic>n =<\/jats:italic>\n                    8) and gene-elusive (GE,\n                    <jats:italic>n =<\/jats:italic>\n                    8), we found that Geno-DT accurately and non-invasively predicted the VT circuit locations for both genotypes (with 100%, 94%, 96% sensitivity, specificity, and accuracy for GE patient group, and 86%, 90%, 89% sensitivity, specificity, and accuracy for\n                    <jats:italic>PKP2<\/jats:italic>\n                    patient group), when compared to VT circuit locations identified during clinical EP studies. Moreover, our results revealed that the underlying VT mechanisms differ among ARVC genotypes. We determined that in GE patients, fibrotic remodeling is the primary contributor to VT circuits, while in\n                    <jats:italic>PKP2<\/jats:italic>\n                    patients, slowed conduction velocity and altered restitution properties of cardiac tissue, in addition to the structural substrate, are directly responsible for the formation of VT circuits. Our novel Geno-DT approach has the potential to augment therapeutic precision in the clinical setting and lead to more personalized treatment strategies in ARVC.\n                  <\/jats:p>","DOI":"10.7554\/elife.88865","type":"journal-article","created":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T06:46:34Z","timestamp":1689662794000},"update-policy":"https:\/\/doi.org\/10.7554\/elife.88865","source":"Crossref","is-referenced-by-count":9,"title":["Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins"],"prefix":"10.7554","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2070-6786","authenticated-orcid":true,"given":"Yingnan","family":"Zhang","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00za53h95","id-type":"ROR","asserted-by":"publisher"}],"name":"Department of Biomedical Engineering, Johns Hopkins University","place":["Baltimore, United 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