{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T08:07:51Z","timestamp":1792829271467,"version":"4.5.0"},"reference-count":43,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T00:00:00Z","timestamp":1709164800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Prediction of major arrhythmic events (MAEs) in dilated cardiomyopathy represents an unmet clinical goal. Computational models and artificial intelligence (AI) are new technological tools that could offer a significant improvement in our ability to predict MAEs. In this proof-of-concept study, we propose a deep learning (DL)-based model, which we termed Deep ARrhythmic Prevention in dilated cardiomyopathy (DARP-D), built using multidimensional cardiac magnetic resonance data (cine videos and hypervideos and LGE images and hyperimages) and clinical covariates, aimed at predicting and tracking an individual patient\u2019s risk curve of MAEs (including sudden cardiac death, cardiac arrest due to ventricular fibrillation, sustained ventricular tachycardia lasting \u226530 s or causing haemodynamic collapse in &lt;30 s, appropriate implantable cardiac defibrillator intervention) over time. The model was trained and validated in 70% of a sample of 154 patients with dilated cardiomyopathy and tested in the remaining 30%. DARP-D achieved a 95% CI in Harrell\u2019s C concordance indices of 0.12\u20130.68 on the test set. We demonstrate that our DL approach is feasible and represents a novelty in the field of arrhythmic risk prediction in dilated cardiomyopathy, able to analyze cardiac motion, tissue characteristics, and baseline covariates to predict an individual patient\u2019s risk curve of major arrhythmic events. However, the low number of patients, MAEs and epoch of training make the model a promising prototype but not ready for clinical usage. Further research is needed to improve, stabilize and validate the performance of the DARP-D to convert it from an AI experiment to a daily used tool.<\/jats:p>","DOI":"10.1371\/journal.pone.0297793","type":"journal-article","created":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T13:28:01Z","timestamp":1709213281000},"page":"e0297793","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":19,"title":["Deep learning-based prediction of major arrhythmic events in dilated cardiomyopathy: A proof of concept study"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4583-280X","authenticated-orcid":true,"given":"Mattia","family":"Corian\u00f2","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Corrado","family":"Lanera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"De Michieli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Perazzolo Marra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabino","family":"Iliceto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dario","family":"Gregori","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Tona","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2024,2,29]]},"reference":[{"key":"pone.0297793.ref001","doi-asserted-by":"crossref","first-page":"3997","DOI":"10.1093\/eurheartj\/ehac262","article-title":"2022 ESC Guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death","volume":"43","author":"K Zeppenfeld","year":"2022","journal-title":"Eur Heart J"},{"key":"pone.0297793.ref002","doi-asserted-by":"crossref","first-page":"1850","DOI":"10.1093\/eurheartj\/ehv727","article-title":"Proposal for a revised definition of dilated cardiomyopathy, hypokinetic non-dilated cardiomyopathy, and its implications for clinical practice: a position statement of the ESC working group on myocardial and pericardial diseases","volume":"37","author":"YM Pinto","year":"2016","journal-title":"Eur Heart J"},{"key":"pone.0297793.ref003","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1161\/01.CIR.80.3.564","article-title":"Epidemiology of idiopathic dilated and hypertrophic cardiomyopathy. A population-based study in Olmsted County, Minnesota, 1975\u20131984","volume":"80","author":"MB Codd","year":"1989","journal-title":"Circulation"},{"key":"pone.0297793.ref004","first-page":"1190","article-title":"Epidemiology of cardiomyopathies: essential context knowledge for a tailored clinical work-up.","volume":"29","author":"D Pasqualucci","year":"2022","journal-title":"Eur J Prev Cardiol"},{"key":"pone.0297793.ref005","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1056\/NEJMoa1608029","article-title":"DANISH Investigators. Defibrillator Implantation in Patients with Nonischemic Systolic Heart Failure","volume":"375","author":"L K\u00f8ber","year":"2016","journal-title":"N Engl J Med"},{"key":"pone.0297793.ref006","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1002\/ejhf.2333","article-title":"2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: Developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC","volume":"24","author":"TA McDonagh","year":"2022","journal-title":"Eur J Heart Fail"},{"key":"pone.0297793.ref007","doi-asserted-by":"crossref","first-page":"2184","DOI":"10.1002\/ehf2.12865","article-title":"Left ventricular midwall fibrosis as a predictor of sudden cardiac death in non-ischaemic dilated cardiomyopathy: a meta-analysis","volume":"7","author":"J Wang","year":"2020","journal-title":"ESC Heart Fail"},{"key":"pone.0297793.ref008","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1161\/CIRCULATIONAHA.116.027134","article-title":"Personalizing Risk Stratification for Sudden Death in Dilated Cardiomyopathy: The Past, Present, and Future","volume":"136","author":"BP Halliday","year":"2017","journal-title":"Circulation"},{"key":"pone.0297793.ref009","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1038\/s44161-022-00041-9","article-title":"Arrhythmic sudden death survival prediction using deep learning analysis of scarring in the heart","volume":"1","author":"DM Popescu","year":"2022","journal-title":"Nat Cardiovasc Res"},{"key":"pone.0297793.ref010","doi-asserted-by":"crossref","first-page":"11437","DOI":"10.1038\/ncomms11437","article-title":"Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models","volume":"7","author":"HJ Arevalo","year":"2016","journal-title":"Nat Commun"},{"issue":"3","key":"pone.0297793.ref011","doi-asserted-by":"crossref","first-page":"639","DOI":"10.3390\/biomedicines10030639","article-title":"Strategies for Sudden Cardiac Death Prevention.","volume":"10","author":"M Corian\u00f2","year":"2022","journal-title":"Biomedicines"},{"key":"pone.0297793.ref012","doi-asserted-by":"crossref","first-page":"e017002","DOI":"10.1161\/JAHA.120.017002","article-title":"Baseline and Dynamic Risk Predictors of Appropriate Implantable Cardioverter Defibrillator Therapy.","volume":"9","author":"KC Wu","year":"2020","journal-title":"JAHA"},{"key":"pone.0297793.ref013","volume-title":"The Elements of Statistical Learning","author":"Springer","year":"2009"},{"key":"pone.0297793.ref014","unstructured":"Shi X, Chen Z, Wang H, Yeung DY, Wong W kin, Woo W chun. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting. Available from: http:\/\/arxiv.org\/abs\/1506.04214."},{"key":"pone.0297793.ref015","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1161\/01.CIR.93.5.841","article-title":"Report of the 1995 World Health Organization\/International Society and Federation of Cardiology Task Force on the Definition and Classification of cardiomyopathies","volume":"93","author":"P Richardson","year":"1996","journal-title":"Circulation"},{"key":"pone.0297793.ref016","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1111\/j.2517-6161.1972.tb00899.x","article-title":"Regression Models and Life-Tables","volume":"34","author":"DR Cox","year":"1972","journal-title":"Journal of the Royal Statistical Society Series B (Methodological)"},{"key":"pone.0297793.ref017","volume-title":"R: A Language and Environment for Statistical Computing","author":"R Core Team","year":"2022"},{"key":"pone.0297793.ref018","year":"2022","journal-title":"Keras: R Interface to \u00abKeras\u00bb"},{"key":"pone.0297793.ref019","year":"2022","journal-title":"Tensorflow: R Interface to \u00abTensorFlow\u00bb"},{"key":"pone.0297793.ref020","doi-asserted-by":"crossref","first-page":"2959","DOI":"10.21105\/joss.02959","article-title":"The targets R package: a dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing","volume":"6","author":"W. M. Landau","year":"2021","journal-title":"Journal of Open Source Software"},{"key":"pone.0297793.ref021","author":"A. Graves","year":"2014","journal-title":"Generating Sequences With Recurrent Neural Networks"},{"key":"pone.0297793.ref022","author":"R Pascanu","year":"2013","journal-title":"On the difficulty of training Recurrent Neural Networks"},{"key":"pone.0297793.ref023","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"Sepp Hochreite, J\u00fcrgen Schmidhuber; Long Short-Term Memory","year":"1997","journal-title":"Neural Comput"},{"key":"pone.0297793.ref024","unstructured":"Neural network recognizer for hand-written zip code digits | Proceedings of the 1st International Conference on Neural Information Processing. Available from: https:\/\/dl.acm.org\/doi\/10.5555\/2969735.2969773"},{"key":"pone.0297793.ref025","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning.","volume":"521","author":"Y LeCun","year":"2015","journal-title":"Nature"},{"key":"pone.0297793.ref026","doi-asserted-by":"crossref","first-page":"292","DOI":"10.3390\/electronics8030292","article-title":"A State-of-the-Art Survey on Deep Learning Theory and Architectures","volume":"8","author":"MZ Alom","year":"2019","journal-title":"Electronics"},{"key":"pone.0297793.ref027","first-page":"1929","article-title":"Dropout: A Simple Way to Prevent Neural Networks from Overfitting","volume":"15","author":"N Srivastava","year":"2014","journal-title":"Journal of Machine Learning Research"},{"key":"pone.0297793.ref028","author":"S Ioffe","year":"2015","journal-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift"},{"issue":"1","key":"pone.0297793.ref029","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1002\/sim.4780140108","article-title":"A neural network model for survival data.","volume":"14","author":"D Faraggi","year":"1995","journal-title":"Stat Med.Jan 15"},{"key":"pone.0297793.ref030","unstructured":"DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network. Available from: https:\/\/bmcmedresmethodol.biomedcentral.com\/articles\/10.1186\/s12874-018-0482-1."},{"key":"pone.0297793.ref031","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1002\/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4","article-title":"Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.","volume":"15","author":"FE Harrell","year":"1996","journal-title":"Stat Med"},{"key":"pone.0297793.ref032","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1161\/CIRCULATIONAHA.116.023042","article-title":"Development and Validation of a Sudden Cardiac Death Prediction Model for the General Population","volume":"134","author":"R Deo","year":"2016","journal-title":"Circulation"},{"key":"pone.0297793.ref033","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1056\/NEJMoa1608029","article-title":"DANISH Investigators. Defibrillator Implantation in Patients with Nonischemic Systolic Heart Failure","volume":"375","author":"L K\u00f8ber","year":"2016","journal-title":"N Engl J Med"},{"key":"pone.0297793.ref034","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1016\/j.hrthm.2014.01.014","article-title":"Impact of the presence and amount of myocardial fibrosis by cardiac magnetic resonance on arrhythmic outcome and sudden cardiac death in nonischemic dilated cardiomyopathy","volume":"11","author":"M Perazzolo Marra","year":"2014","journal-title":"Heart Rhythm"},{"key":"pone.0297793.ref035","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1016\/j.jcmg.2018.07.015","article-title":"Outcome in Dilated Cardiomyopathy Related to the Extent, Location, and Pattern of Late Gadolinium Enhancement.","volume":"12","author":"BP Halliday","year":"2019","journal-title":"JACC Cardiovasc Imaging"},{"key":"pone.0297793.ref036","doi-asserted-by":"crossref","first-page":"2129","DOI":"10.1093\/eurheartj\/ehw128","article-title":"2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.","volume":"37","author":"P Ponikowski","year":"2016","journal-title":"Eur Heart J"},{"key":"pone.0297793.ref037","author":"Q Meng","year":"2022","journal-title":"MulViMotion: Shape-aware 3D Myocardial Motion Tracking from Multi-View Cardiac MRI"},{"key":"pone.0297793.ref038","doi-asserted-by":"crossref","first-page":"4831","DOI":"10.1093\/eurheartj\/ehad727","article-title":"Five critical quality criteria for artificial intelligence-based prediction models","volume":"44","author":"FS Van Royen","year":"2023","journal-title":"European Heart Journal"},{"key":"pone.0297793.ref039","doi-asserted-by":"crossref","first-page":"2921","DOI":"10.1093\/eurheartj\/ehac238","article-title":"Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease","volume":"43","author":"M Van Smeden","year":"2022","journal-title":"European Heart Journal"},{"key":"pone.0297793.ref040","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1016\/j.jacc.2018.06.037","article-title":"Present Status of Brugada Syndrome: JACC State-of-the-Art Review","volume":"72","author":"J Brugada","year":"2018","journal-title":"Journal of the American College of Cardiology"},{"key":"pone.0297793.ref041","doi-asserted-by":"crossref","first-page":"2095","DOI":"10.1111\/jce.16045","article-title":"Athletes and suspected catecholaminergic polymorphic ventricular tachycardia: Awareness and current knowledge","volume":"34","author":"G Mascia","year":"2023","journal-title":"Journal of Cardiovascular Electrophysiology"},{"key":"pone.0297793.ref042","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.ijcard.2021.11.029","article-title":"Comparative Assessment of Transvenous versus Subcutaneous Implantable Cardioverter-defibrillator Therapy Outcomes: An Updated Systematic Review and Meta-analysis.","volume":"349","author":"N Nso","year":"2022","journal-title":"Int J Cardiol."},{"key":"pone.0297793.ref043","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1007\/s00380-022-02204-x","article-title":"Subcutaneous versus transvenous implantable cardioverter-defibrillator among drug-induced type-1 ECG pattern Brugada syndrome: a propensity score matching analysis from IBRYD study","volume":"38","author":"V Russo","year":"2023","journal-title":"Heart Vessels"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0297793","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T13:28:34Z","timestamp":1709213314000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0297793"}},"subtitle":[],"editor":[{"given":"Vincenzo","family":"Lionetti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,2,29]]},"references-count":43,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,2,29]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0297793","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,29]]}}}