{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:43:02Z","timestamp":1753875782810,"version":"3.41.2"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T00:00:00Z","timestamp":1729036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Japanese Agency for Medical Research and Development","award":["JP18km0405209","JP19ek0210118","JP21ek0109543","JP22ama121016","JP22ek0210172","JP22bm1123011","JP23gm4010020","JP223fa627011","JP23tm0524009","JP23tm0524004","JP23jf0126003","JP24ek0109755","JP24ek0210205"],"award-info":[{"award-number":["JP18km0405209","JP19ek0210118","JP21ek0109543","JP22ama121016","JP22ek0210172","JP22bm1123011","JP23gm4010020","JP223fa627011","JP23tm0524009","JP23tm0524004","JP23jf0126003","JP24ek0109755","JP24ek0210205"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Heart failure (HF), a major cause of morbidity and mortality, necessitates precise diagnostic and prognostic methods.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>This study presents a novel deep learning approach, Transformer-based Analysis of Images of Tissue for Effective Remedy (TRAITER), for HF diagnosis and prognosis. Using image segmentation techniques and a Vision Transformer, TRAITER predicts HF likelihood from cardiac tissue cell nuclear morphology images and the potential for left ventricular reverse remodeling (LVRR) from dual-stained images with cell nuclei and DNA damage markers. In HF prediction using 31\u00a0158 images from 9 patients, TRAITER achieved 83.1% accuracy. For LVRR prediction with 231\u00a0840 images from 46 patients, TRAITER attained 84.2% accuracy for individual images and 92.9% for individual patients. TRAITER outperformed other neural network models in terms of receiver operating characteristics, and precision\u2013recall curves. Our method promises to advance personalized HF medicine decision-making.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The source code and data are available at the following link: https:\/\/github.com\/HamanoLaboratory\/predict-of-HF-and-LVRR.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae610","type":"journal-article","created":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T14:31:26Z","timestamp":1729089086000},"source":"Crossref","is-referenced-by-count":0,"title":["TRAITER: transformer-guided diagnosis and prognosis of heart failure using cell nuclear morphology and DNA damage marker"],"prefix":"10.1093","volume":"40","author":[{"given":"Hiromu","family":"Hayashi","sequence":"first","affiliation":[{"name":"Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka 820-8502, Fukuoka,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Toshiyuki","family":"Ko","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]},{"name":"Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0363-7563","authenticated-orcid":false,"given":"Zhehao","family":"Dai","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kanna","family":"Fujita","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]},{"name":"Department of Computational Diagnostic Radiology and Preventive Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seitaro","family":"Nomura","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]},{"name":"Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroki","family":"Kiyoshima","sequence":"additional","affiliation":[{"name":"Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka 820-8502, Fukuoka,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shinya","family":"Ishihara","sequence":"additional","affiliation":[{"name":"Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka 820-8502, Fukuoka,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8752-7053","authenticated-orcid":false,"given":"Momoko","family":"Hamano","sequence":"additional","affiliation":[{"name":"Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka 820-8502, Fukuoka,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Issei","family":"Komuro","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Medicine, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]},{"name":"Department of Frontier Cardiovascular Science, Graduate School of Medicine, The University of Tokyo , Bunkyo, Tokyo 113-8655,","place":["Japan"]},{"name":"International University of Health and Welafare , Minato, Tokyo 107-8402,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoshihiro","family":"Yamanishi","sequence":"additional","affiliation":[{"name":"Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka 820-8502, Fukuoka,","place":["Japan"]},{"name":"Department of Complex Systems Science, Graduate School of Informatics, Nagoya University , Chikusa, Nagoya, Aichi 464-8601,","place":["Japan"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,10,16]]},"reference":[{"key":"2024111117062931900_btae610-B1","article-title":"Image processing with imageJ","volume":"11","author":"Abr\u00e0moff","year":"2004","journal-title":"Biophotonics Int"},{"key":"2024111117062931900_btae610-B2","doi-asserted-by":"crossref","first-page":"e56","DOI":"10.1161\/CIR.0000000000000659","article-title":"Heart disease and stroke statistics-2019 update: a report from the American heart association","volume":"139","author":"Benjamin","year":"2019","journal-title":"Circulation"},{"key":"2024111117062931900_btae610-B3","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1016\/S0140-6736(14)61889-4","article-title":"The war against heart failure: the Lancet lecture","volume":"385","author":"Braunwald","year":"2015","journal-title":"Lancet"},{"key":"2024111117062931900_btae610-B4","doi-asserted-by":"crossref","first-page":"1001002","DOI":"10.3389\/fcvm.2022.1001002","article-title":"Donor shortage in heart transplantation: how can we overcome this challenge?","volume":"9","author":"Cameli","year":"2022","journal-title":"Front Cardiovasc Med"},{"key":"2024111117062931900_btae610-B5","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1016\/j.jchf.2023.09.027","article-title":"Myocardial DNA damage predicts heart failure outcome in various underlying diseases","volume":"12","author":"Dai","year":"2024","journal-title":"JACC Heart Fail"},{"key":"2024111117062931900_btae610-B6","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1016\/j.ejheart.2008.08.005","article-title":"ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008","volume":"10","author":"Dickstein","journal-title":"Eur J Heart Fail"},{"year":"2021","author":"Dosovitskiy","key":"2024111117062931900_btae610-B7"},{"key":"2024111117062931900_btae610-B8","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1109\/TPAMI.1987.4767941","article-title":"Image analysis using mathematical morphology","volume":"9","author":"Haralick","year":"1987","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"year":"2016","author":"He","key":"2024111117062931900_btae610-B9"},{"key":"2024111117062931900_btae610-B10","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1038\/s43587-022-00263-3","article-title":"Nuclear morphology is a deep learning biomarker of cellular senescence","volume":"2","author":"Heckenbach","year":"2022","journal-title":"Nat Aging"},{"key":"2024111117062931900_btae610-B11","doi-asserted-by":"crossref","first-page":"2996","DOI":"10.1016\/j.jacc.2016.03.590","article-title":"The diagnosis and evaluation of dilated cardiomyopathy","volume":"67","author":"Japp","year":"2016","journal-title":"J Am Coll Cardiol"},{"key":"2024111117062931900_btae610-B12","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1038\/s41746-023-00795-x","article-title":"Weakly supervised deep learning to predict recurrence in low-grade endometrial cancer from multiplexed immunofluorescence images","volume":"6","author":"Jim\u00e9nez-S\u00e1nchez","year":"2023","journal-title":"NPJ Digit Med"},{"key":"2024111117062931900_btae610-B13","doi-asserted-by":"crossref","first-page":"5409","DOI":"10.1038\/s41467-019-13163-9","article-title":"Brain age prediction using deep learning uncovers associated sequence variants","volume":"10","author":"Jonsson","year":"2019","journal-title":"Nat Commun"},{"key":"2024111117062931900_btae610-B14","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1536\/ihj.21-407","article-title":"The effectiveness of a deep learning model to detect left ventricular systolic dysfunction from electrocardiograms","volume":"62","author":"Katsushika","year":"2021","journal-title":"Int Heart J"},{"key":"2024111117062931900_btae610-B15","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1111\/ajt.13055","article-title":"National decline in donor heart utilization with regional variability: 1995-2010","volume":"15","author":"Khush","year":"2015","journal-title":"Am J Transplant"},{"key":"2024111117062931900_btae610-B16","doi-asserted-by":"crossref","first-page":"670","DOI":"10.1016\/j.jacbts.2019.05.010","article-title":"Quantification of DNA damage in heart tissue as a novel prediction tool for therapeutic prognosis of patients with dilated cardiomyopathy","volume":"4","author":"Ko","year":"2019","journal-title":"JACC Basic Transl Sci"},{"key":"2024111117062931900_btae610-B17","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","article-title":"A survey on deep learning in medical image analysis","volume":"42","author":"Litjens","year":"2017","journal-title":"Med Image Anal"},{"key":"2024111117062931900_btae610-B18","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.amjcard.2012.08.056","article-title":"Left ventricular reverse remodeling in long-term (&gt;12 years) survivors with idiopathic dilated cardiomyopathy","volume":"111","author":"Matsumura","year":"2013","journal-title":"Am J Cardiol"},{"key":"2024111117062931900_btae610-B19","first-page":"5521","article-title":"Comparing vision transformers and convolutional neural networks for image classification: A literature review","volume":"13","author":"Maur\u00edcio","year":"2023","journal-title":"Appl Sci (Switzerland)"},{"key":"2024111117062931900_btae610-B20","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1016\/j.jacc.2011.05.033","article-title":"Clinical and demographic predictors of outcomes in recent onset dilated cardiomyopathy: results of the IMAC (intervention in myocarditis and acute cardiomyopathy)-2 study","volume":"58","author":"McNamara","year":"2011","journal-title":"J Am Coll Cardiol"},{"key":"2024111117062931900_btae610-B21","doi-asserted-by":"crossref","first-page":"e001504","DOI":"10.1161\/JAHA.114.001504","article-title":"Persistent recovery of normal left ventricular function and dimension in idiopathic dilated cardiomyopathy during long-term follow-up: does real healing exist?","volume":"4","author":"Merlo","year":"2015","journal-title":"J Am Heart Assoc"},{"key":"2024111117062931900_btae610-B22","doi-asserted-by":"crossref","first-page":"1468","DOI":"10.1016\/j.jacc.2010.11.030","article-title":"Prevalence and prognostic significance of left ventricular reverse remodeling in dilated cardiomyopathy receiving tailored medical treatment","volume":"57","author":"Merlo","year":"2011","journal-title":"J Am Coll Cardiol"},{"key":"2024111117062931900_btae610-B23","doi-asserted-by":"crossref","first-page":"1981","DOI":"10.1016\/S0140-6736(17)31071-1","article-title":"Lancet review heart failure","volume":"390","author":"Metra","year":"2017","journal-title":"The Lancet"},{"key":"2024111117062931900_btae610-B24","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1253\/circj.72.489","article-title":"Impending epidemic\u2014future projection of heart failure in Japan to the year 2055","volume":"72","author":"Okura","year":"2008","journal-title":"Circ J"},{"key":"2024111117062931900_btae610-B25","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1996","journal-title":"IEEE Trans Syst Man Cybernet"},{"key":"2024111117062931900_btae610-B26","doi-asserted-by":"crossref","first-page":"106035","DOI":"10.1016\/j.biocel.2021.106035","article-title":"The NUCLEUS: mechanosensing in cardiac disease","volume":"137","author":"Ross","year":"2021","journal-title":"Int J Biochem Cell Biol"},{"key":"2024111117062931900_btae610-B27","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","article-title":"ImageNet large scale visual recognition challenge","volume":"115","author":"Russakovsky","year":"2015","journal-title":"Int J Comput Vis"},{"key":"2024111117062931900_btae610-B28","article-title":"A comprehensive guide to convolutional neural networks\u2013the ELI5 way | by sumit Saha | towards data science","author":"Saha","year":"2018","journal-title":"Towards Data Sci"},{"key":"2024111117062931900_btae610-B29","first-page":"7","article-title":"Division of Cardiology, Department of Medicine, Karolinska Insitutet, Stockholm, Sweden Epidemiology global public health burden of heart failure","volume":"03","author":"Savarese","year":"2017","journal-title":"CRF J"},{"key":"2024111117062931900_btae610-B30","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.jjcc.2021.08.029","article-title":"Deep learning model to detect significant aortic regurgitation using electrocardiography","volume":"79","author":"Sawano","year":"2022","journal-title":"J Cardiol"},{"key":"2024111117062931900_btae610-B31","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/S0002-9149(83)80088-5","article-title":"Quantitative morphologic findings of the myocardium in idiopathic dilated cardiomyopathy","volume":"51","author":"Schwarz","year":"1983","journal-title":"Am J Cardiol"},{"year":"2017","author":"Szegedy","key":"2024111117062931900_btae610-B32"},{"key":"2024111117062931900_btae610-B33","doi-asserted-by":"crossref","first-page":"e531","DOI":"10.1097\/MJT.0000000000000406","article-title":"Treatment of heart failure with reduced ejection fraction\u2014recent developments","volume":"23","author":"Travessa","year":"2016","journal-title":"Am J Ther"},{"key":"2024111117062931900_btae610-B34","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1016\/S0140-6736(17)32154-2","article-title":"Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990-2016: a systematic analysis for the global burden of disease study 2016","volume":"390","author":"Vos","year":"2017","journal-title":"The Lancet"},{"key":"2024111117062931900_btae610-B35","doi-asserted-by":"crossref","first-page":"eade7047","DOI":"10.1126\/sciadv.ade7047","article-title":"TEAD1 trapping by the Q353R\u2013Lamin a\/C causes dilated cardiomyopathy","volume":"9","author":"Yamada","year":"2023","journal-title":"Sci Adv"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae610\/59809596\/btae610.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/11\/btae610\/60592573\/btae610.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/11\/btae610\/60592573\/btae610.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T17:07:30Z","timestamp":1731344850000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btae610\/7824057"}},"subtitle":[],"editor":[{"given":"Hanchuan","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2024,10,16]]},"references-count":35,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2024,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btae610","relation":{},"ISSN":["1367-4811"],"issn-type":[{"type":"electronic","value":"1367-4811"}],"subject":[],"published-other":{"date-parts":[[2024,11]]},"published":{"date-parts":[[2024,10,16]]},"article-number":"btae610"}}