{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T15:54:46Z","timestamp":1792684486021,"version":"4.5.0"},"reference-count":34,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100002784","name":"Canada Excellence Research Chairs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002784","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","jacc.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["JACC: Cardiovascular Imaging"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.jcmg.2026.04.007","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T20:50:00Z","timestamp":1780001400000},"page":"1043-1054","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":3,"title":["Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac Dysfunction"],"prefix":"10.1016","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1025-5480","authenticated-orcid":false,"given":"Christopher","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Peikari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dina","family":"Labib","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian P.","family":"Houbois","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun-Po","family":"Steve Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James A.","family":"White","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eitan","family":"Amir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3077-2218","authenticated-orcid":false,"given":"Kate","family":"Hanneman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernd","family":"J. Wintersperger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Husam","family":"Abdel-Qadir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1371-1250","authenticated-orcid":false,"given":"Chris","family":"McIntosh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paaladinesh","family":"Thavendiranathan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.jcmg.2026.04.007_bib1","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1001\/jamacardio.2023.0494","article-title":"Comprehensive cardiovascular magnetic resonance tissue characterization and cardiotoxicity in women with breast cancer","volume":"8","author":"Thavendiranathan","year":"2023","journal-title":"JAMA Cardiol"},{"issue":"41","key":"10.1016\/j.jcmg.2026.04.007_bib2","doi-asserted-by":"crossref","first-page":"4229","DOI":"10.1093\/eurheartj\/ehac244","article-title":"2022 ESC guidelines on cardio-oncology developed in collaboration with the European Hematology Association (EHA), the European Society for Therapeutic Radiology and Oncology (ESTRO) and the International Cardio-Oncology Society (IC-OS)","volume":"43","author":"Lyon","year":"2022","journal-title":"Eur Heart J"},{"issue":"3","key":"10.1016\/j.jcmg.2026.04.007_bib3","doi-asserted-by":"crossref","first-page":"847","DOI":"10.3390\/jcm11030847","article-title":"Evaluation of risk prediction models to identify cancer therapeutics related cardiac dysfunction in women with HER2+ breast cancer","volume":"11","author":"Suntheralingam","year":"2022","journal-title":"J Clin Med"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib4","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1007\/s10549-021-06192-w","article-title":"Incidence of cardiotoxicity and validation of the Heart Failure Association-International Cardio-Oncology Society risk stratification tool in patients treated with trastuzumab for HER2-positive early breast cancer","volume":"188","author":"Battisti","year":"2021","journal-title":"Breast Cancer Res Treat"},{"issue":"10","key":"10.1016\/j.jcmg.2026.04.007_bib5","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1001\/jamacardio.2019.2952","article-title":"Assessment of prognostic value of left ventricular global longitudinal strain for early prediction of chemotherapy-induced cardiotoxicity: a systematic review and meta-analysis","volume":"4","author":"Oikonomou","year":"2019","journal-title":"JAMA Cardiol"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib6","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/S0002-9149(02)02381-0","article-title":"Comparison of interstudy reproducibility of cardiovascular magnetic resonance with two-dimensional echocardiography in normal subjects and in patients with heart failure or left ventricular hypertrophy","volume":"90","author":"Grothues","year":"2002","journal-title":"Am J Cardiol"},{"issue":"3","key":"10.1016\/j.jcmg.2026.04.007_bib7","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1001\/jamacardio.2021.5881","article-title":"A combined echocardiography approach for the diagnosis of cancer therapy-related cardiac dysfunction in women with early-stage breast cancer","volume":"7","author":"Esmaeilzadeh","year":"2022","journal-title":"JAMA Cardiol"},{"issue":"4","key":"10.1016\/j.jcmg.2026.04.007_bib8","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1001\/jamacardio.2021.6059","article-title":"High-throughput precision phenotyping of left ventricular hypertrophy with cardiovascular deep learning","volume":"7","author":"Duffy","year":"2022","journal-title":"JAMA Cardiol"},{"issue":"43","key":"10.1016\/j.jcmg.2026.04.007_bib9","doi-asserted-by":"crossref","first-page":"4592","DOI":"10.1093\/eurheartj\/ehad456","article-title":"Severe aortic stenosis detection by deep learning applied to echocardiography","volume":"44","author":"Holste","year":"2023","journal-title":"Eur Heart J"},{"issue":"9","key":"10.1016\/j.jcmg.2026.04.007_bib10","doi-asserted-by":"crossref","DOI":"10.1161\/JAHA.120.019811","article-title":"Effect of active cancer on the cardiac phenotype: a cardiac magnetic resonance imaging-based study of myocardial tissue health and deformation in patients with chemotherapy-naive cancer","volume":"10","author":"Labib","year":"2021","journal-title":"J Am Heart Assoc"},{"issue":"6","key":"10.1016\/j.jcmg.2026.04.007_bib11","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1093\/ehjcvp\/pvad031","article-title":"Statins to prevent early cardiac dysfunction in cancer patients at increased cardiotoxicity risk receiving anthracyclines","volume":"9","author":"Thavendiranathan","year":"2023","journal-title":"Eur Heart J Cardiovasc Pharmacother"},{"issue":"11","key":"10.1016\/j.jcmg.2026.04.007_bib12","doi-asserted-by":"crossref","first-page":"1945","DOI":"10.1002\/ejhf.1920","volume":"22","author":"Lyon","year":"2020","journal-title":"Eur J Heart Fail"},{"issue":"5","key":"10.1016\/j.jcmg.2026.04.007_bib13","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1200\/JCO.2002.20.5.1215","article-title":"Cardiac dysfunction in the trastuzumab clinical trials experience","volume":"20","author":"Seidman","year":"2002","journal-title":"J Clin Oncol"},{"issue":"36","key":"10.1016\/j.jcmg.2026.04.007_bib14","doi-asserted-by":"crossref","first-page":"2768","DOI":"10.1093\/eurheartj\/ehw211","article-title":"2016 ESC position paper on cancer treatments and cardiovascular toxicity developed under the auspices of the ESC Committee for Practice Guidelines: the Task Force for Cancer Treatments and Cardiovascular Toxicity of the European Society of Cardiology (ESC)","volume":"37","author":"Zamorano","year":"2016","journal-title":"Eur Heart J"},{"issue":"3","key":"10.1016\/j.jcmg.2026.04.007_bib15","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/72.761722","article-title":"Fast and robust fixed-point algorithms for independent component analysis","volume":"10","author":"Hyvarinen","year":"1999","journal-title":"IEEE Trans Neural Netw"},{"key":"10.1016\/j.jcmg.2026.04.007_bib16","series-title":"Very deep convolutional networks for large-scale image recognition","first-page":"1409","author":"Simonyan","year":"2014"},{"key":"10.1016\/j.jcmg.2026.04.007_bib17","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1109\/JPROC.2015.2494218","article-title":"Taking the human out of the loop: a review of Bayesian optimization","volume":"104","author":"Shahriari","year":"2016","journal-title":"Proc IEEE"},{"key":"10.1016\/j.jcmg.2026.04.007_bib18","author":"Nogueira"},{"issue":"2","key":"10.1016\/j.jcmg.2026.04.007_bib19","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.jcmg.2025.08.004","article-title":"PRIME 2.0: proposed requirements for cardiovascular imaging-related multimodal-AI evaluation","volume":"19","author":"Kagiyama","year":"2026","journal-title":"JACC Cardiovasc Imaging"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib20","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1186\/s12968-019-0567-y","article-title":"Quantification of lung water in heart failure using cardiovascular magnetic resonance imaging","volume":"21","author":"Thompson","year":"2019","journal-title":"J Cardiovasc Magn Reson"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.echo.2014.10.003","article-title":"Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging","volume":"28","author":"Lang","year":"2015","journal-title":"J Am Soc Echocardiogr"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib22","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s12968-020-00610-6","article-title":"Standardized image interpretation and post-processing in cardiovascular magnetic resonance\u20142020 update: society for Cardiovascular Magnetic Resonance (SCMR): board of Trustees Task Force on standardized Post-Processing","volume":"22","author":"Schulz-Menger","year":"2020","journal-title":"J Cardiovasc Magn Reson"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib23","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jaccao.2020.01.007","article-title":"Early detection and prediction of anthracycline-induced right ventricular cardiotoxicity by 3-dimensional echocardiography","volume":"2","author":"Zhao","year":"2020","journal-title":"JACC CardioOncol"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib24","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s12947-020-00210-5","article-title":"Left atrial longitudinal strain as a predictor of cancer therapeutics\u2013related cardiac dysfunction in patients with breast cancer","volume":"18","author":"Park","year":"2020","journal-title":"Cardiovasc Ultrasound"},{"issue":"11","key":"10.1016\/j.jcmg.2026.04.007_bib25","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1016\/j.echo.2025.07.012","article-title":"Whole-heart changes during cancer therapy and their potential relevance in women with breast cancer","volume":"38","author":"Sooriyakanthan","year":"2025","journal-title":"J Am Soc Echocardiogr"},{"issue":"9","key":"10.1016\/j.jcmg.2026.04.007_bib26","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1038\/s41569-024-01017-x","article-title":"Cardiovascular disease and cancer: shared risk factors and mechanisms","volume":"21","author":"Wilcox","year":"2024","journal-title":"Nat Rev Cardiol"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib27","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1038\/s41746-024-01118-4","article-title":"Shortcut learning in medical AI hinders generalization: method for estimating AI model generalization without external data","volume":"7","author":"Ong Ly","year":"2024","journal-title":"NPJ Digit Med"},{"issue":"3","key":"10.1016\/j.jcmg.2026.04.007_bib28","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.210064","article-title":"External validation of deep learning algorithms for radiologic diagnosis: a systematic review","volume":"4","author":"Yu","year":"2022","journal-title":"Radiol Artif Intell"},{"issue":"6","key":"10.1016\/j.jcmg.2026.04.007_bib29","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1016\/j.jcmg.2024.01.008","article-title":"Utility of baseline left atrial reservoir strain in predicting cardiotoxicity after chemotherapy: a SUCCOUR study subanalysis","volume":"17","author":"Yu","year":"2024","journal-title":"JACC Cardiovasc Imaging"},{"issue":"3","key":"10.1016\/j.jcmg.2026.04.007_bib30","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1093\/eurheartj\/ehae496","article-title":"Anthracycline-induced cardiovascular toxicity: validation of the Heart Failure Association and International Cardio-Oncology Society risk score","volume":"46","author":"Rivero-Santana","year":"2025","journal-title":"Eur Heart J"},{"issue":"5","key":"10.1016\/j.jcmg.2026.04.007_bib31","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1016\/j.jcmg.2020.09.039","article-title":"Serial cardiovascular magnetic resonance strain measurements to identify cardiotoxicity in breast cancer: comparison with echocardiography","volume":"14","author":"Houbois","year":"2021","journal-title":"JACC Cardiovasc Imaging"},{"issue":"12","key":"10.1016\/j.jcmg.2026.04.007_bib32","doi-asserted-by":"crossref","first-page":"1971","DOI":"10.1001\/jamaoncol.2020.4749","article-title":"Early trastuzumab interruption and recurrence-free survival in ERBB2-positive breast cancer","volume":"6","author":"Copeland-Halperin","year":"2020","journal-title":"JAMA Oncol"},{"issue":"21","key":"10.1016\/j.jcmg.2026.04.007_bib33","doi-asserted-by":"crossref","first-page":"3429","DOI":"10.1200\/JCO.2009.26.7294","article-title":"Role of three-dimensional echocardiography in breast cancer: comparison with two-dimensional echocardiography, multiple-gated acquisition scans, and cardiac magnetic resonance imaging","volume":"28","author":"Walker","year":"2010","journal-title":"J Clin Oncol"},{"issue":"1","key":"10.1016\/j.jcmg.2026.04.007_bib34","doi-asserted-by":"crossref","first-page":"2536","DOI":"10.1038\/s41467-024-45733-x","article-title":"Artificial intelligence-enabled prediction of chemotherapy-induced cardiotoxicity from baseline electrocardiograms","volume":"15","author":"Yagi","year":"2024","journal-title":"Nat Commun"}],"container-title":["JACC: Cardiovascular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1936878X26002299?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1936878X26002299?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T20:08:41Z","timestamp":1788898121000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1936878X26002299"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":34,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["S1936878X26002299"],"URL":"https:\/\/doi.org\/10.1016\/j.jcmg.2026.04.007","relation":{},"ISSN":["1936-878X"],"issn-type":[{"value":"1936-878X","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Machine Learning Model Using Pre-Cancer Therapy Cardiac Magnetic Resonance Images to Predict Cancer Therapy-Related Cardiac Dysfunction","name":"articletitle","label":"Article Title"},{"value":"JACC: Cardiovascular Imaging","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jcmg.2026.04.007","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 by the American College of Cardiology Foundation. Published by Elsevier.","name":"copyright","label":"Copyright"}]}}