{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:04:22Z","timestamp":1792785862838,"version":"4.5.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000589","name":"Chief Scientist Office","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000589","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Scottish Government Health and Social Care Directorates","award":["CZH\/4\/588"],"award-info":[{"award-number":["CZH\/4\/588"]}],"id":[{"id":"https:\/\/ror.org\/01bw7zm61","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Edinburgh and Lothian\u2019s Health Foundation Trust","id":[{"id":"https:\/\/ror.org\/024whdm10","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Heart Diseases Research Fund"},{"name":"Cambridge Trust Scholarship"},{"name":"Royal Brompton Hospital Charity Fellowship","id":[{"id":"https:\/\/ror.org\/00cv4n034","id-type":"ROR","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006662","name":"NIHR","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006662","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018956","name":"NIHR Cambridge Biomedical Research Centre","doi-asserted-by":"publisher","award":["NIHR203312"],"award-info":[{"award-number":["NIHR203312"]}],"id":[{"id":"10.13039\/501100018956","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018956","name":"NIHR Cambridge Biomedical Research Centre","doi-asserted-by":"publisher","award":["BRC-1215-20014"],"award-info":[{"award-number":["BRC-1215-20014"]}],"id":[{"id":"10.13039\/501100018956","id-type":"DOI","asserted-by":"publisher"}]},{"name":"British Heart Foundation Centre of Research Excellence","award":["RE\/24\/130011"],"award-info":[{"award-number":["RE\/24\/130011"]}],"id":[{"id":"https:\/\/ror.org\/02wdwnk04","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Cardiac computed tomography angiography (CTA) is widely used to assess coronary artery disease, but the prognostic value of myocardial radiomic phenotypes beyond coronary artery findings remains unknown.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To investigate whether myocardial radiomic phenotypes derived from cardiac CTA provide incremental prognostic value for fatal or nonfatal myocardial infarction (MI) during long-term follow-up.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>Post hoc analysis of CTA was performed within the Scottish Computed Tomography of the Heart (SCOT-HEART) trial. A multivariable linear regression model was built to assess associations between myocardial radiomic phenotypes and cardiovascular risk factors, including hypertension, diabetes, and calcium score. Univariable and multivariable Cox proportional hazards models were used to determine the associations between myocardial radiomic phenotypes and MI. The prognostic model incorporating myocardial radiomic phenotypes was compared to clinical models based on cardiovascular risk factors, calcium score, and presence of obstructive disease to determine the improvement in predictive performance. Over a median follow-up of 8.6 years, 82 of 1736 participants (4.7%) experienced a fatal or non-fatal MI. Myocardial radiomic phenotypes were associated with age, sex, hypertension, and diabetes (P &amp;lt; 0.01 for all), with older age, male sex, and cardiometabolic risk linked to increased myocardial volume and density. Among myocardial radiomic features associated with cardiovascular risk factors, univariable analysis identified 22 features associated with MI. Incorporation of myocardial radiomic phenotypes into a clinical model (including cardiovascular risk score, CAC score and presence of obstructive disease) improved discrimination for future MI events (C-index from 0.693 to 0.722, \u0394 = 0.029, P &amp;lt; 0.001) and improved model fit (likelihood ratio test, \u03c72 = 13.5, P = 0.009).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Myocardial radiomic phenotypes based on CTA may offer incremental prognostic value for long-term MI prediction, beyond conventional established cardiovascular risk factors and imaging features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>ClinicalTrials.gov Identifier: NCT01149590<\/jats:p>\n                  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