{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,21]],"date-time":"2026-06-21T18:47:39Z","timestamp":1782067659275,"version":"3.54.5"},"reference-count":27,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"6","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Cardiovascular Imaging"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>End-stage hypertrophic cardiomyopathy (HCM) is a distinct and advanced form of HCM, defined by a left ventricular ejection fraction &lt;50% and associated with a markedly poor prognosis. Evidence on the prognostic relevance of late gadolinium enhancement (LGE) and its key features in end-stage HCM remains limited. The aim of our study was to evaluate the prognostic value of the LGE granularity model, including its location, extent, and pattern in patients with end-stage HCM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>All patients referred for cardiovascular magnetic resonance assessment of HCM at 3 French tertiary university hospitals between 2008 and 2024 were retrospectively screened, and all patients with a left ventricular ejection fraction &lt;50% were included. The LGE granularity model was defined as a model combining LGE extent (unique versus multiple involvement), location (septal versus other), and pattern (subepicardial versus midwall). The primary end point was all-cause mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>\n                      Among 2873 patients with HCM, 691 (24%) with end-stage HCM were included (52\u00b17 years, 54% male). After a median follow-up of 9 years (interquartile range, 6\u201311), 226 patients died (33%). LGE was observed in 259 (37%) patients and was associated with mortality, even after adjustment for classical prognostic factors (hazard ratio, 1.52 [95% CI, 1.07\u20132.18];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.02). Each LGE granularity component was independently associated with mortality after adjustment: LGE extent (hazard ratio, 2.85 [95% CI, 1.03\u20137.85];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.02), septal location (hazard ratio, 1.73 [95% CI, 1.10\u20132.73];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.001), and midwall pattern (hazard ratio, 4.15 [95% CI, 1.79\u20139.61];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>In this large multicenter cohort of patients with end-stage HCM, the LGE granularity model integrating LGE extent, location, and pattern provided strong and independent prognostic value.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/circimaging.125.019408","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T09:00:40Z","timestamp":1779440440000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Prognostic Impact of LGE Granularity Using CMR in End\u2011Stage Hypertrophic Cardiomyopathy"],"prefix":"10.1161","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6596-8538","authenticated-orcid":true,"given":"Julien","family":"Hudelo","sequence":"first","affiliation":[{"name":"Department of Cardiology, Amiens University Hospital, France (J.H., C.T., A.H., Y.B.)."},{"name":"Universit\u00e9 Paris Cit\u00e9, Department of Cardiology, University Hospital of Lariboisiere, France (J.H., S.T., T.G., A.U., J.F., J.-G.D., T.P.)."},{"name":"Universit\u00e9 Paris Cit\u00e9, Inserm MASCOT \u2013 UMRS 942, University Hospital of Lariboisiere, France (J.H., S.T., T.G., A.U., J.F., J.-G.D., T.P.)."},{"name":"MIRACL.ai laboratory, Multimodality Imaging for Research and Artificial Intelligence Core Laboratory (J.H., J.G., S.T., T.G., A.U., J.F., J.-G.D., T.P., Y.B.), University Hospital of Lariboisiere (AP-HP), Paris, France."},{"name":"DATA-TEMPLE Laboratory, Department of Data Science, Machine Learning and Artificial Intelligence in Health (J.H., S.T., T.G., A.U., J.F., J.-G.D., T.P.), University Hospital of Lariboisiere (AP-HP), Paris, France."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3714-1256","authenticated-orcid":true,"given":"J\u00e9r\u00f4me","family":"Garot","sequence":"additional","affiliation":[{"name":"MIRACL.ai laboratory, Multimodality Imaging for Research and Artificial Intelligence Core Laboratory (J.H., J.G., S.T., T.G., A.U., J.F., J.-G.D., T.P., Y.B.), University Hospital of Lariboisiere (AP-HP), Paris, France."},{"name":"Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, H\u00f4pital Priv\u00e9 Jacques CARTIER, Ramsay Sant\u00e9, Massy, France (J.G., S.D., F.S., P.G., T.H., S.C., T.U., M.A., A.N., T.G.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9967-0044","authenticated-orcid":true,"given":"Solenn","family":"Toupin","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Paris Cit\u00e9, Department of Cardiology, University Hospital of Lariboisiere, France (J.H., S.T., T.G., A.U., J.F., J.-G.D., T.P.)."},{"name":"Universit\u00e9 Paris Cit\u00e9, Inserm MASCOT \u2013 UMRS 942, University Hospital of Lariboisiere, France (J.H., S.T., T.G., A.U., J.F., J.-G.D., T.P.)."},{"name":"MIRACL.ai laboratory, Multimodality Imaging for Research and Artificial Intelligence Core Laboratory (J.H., J.G., S.T., T.G., A.U., J.F., J.-G.D., T.P., Y.B.), University Hospital of Lariboisiere (AP-HP), Paris, France."},{"name":"DATA-TEMPLE Laboratory, Department of Data Science, Machine Learning and 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