{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T18:01:04Z","timestamp":1780077664085,"version":"3.54.0"},"reference-count":34,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Circ: Cardiovascular Imaging"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:sec>\n            <jats:title>BACKGROUND:<\/jats:title>\n            <jats:p>Right ventricular (RV) function has a well-established prognostic role in patients with severe mitral regurgitation (MR) undergoing transcatheter edge-to-edge repair (TEER) and is typically assessed using echocardiography-measured tricuspid annular plane systolic excursion. Recently, a deep learning model has been proposed that accurately predicts RV ejection fraction (RVEF) from 2-dimensional echocardiographic videos, with similar diagnostic accuracy as 3-dimensional imaging. This study aimed to evaluate the prognostic value of the deep learning\u2013predicted RVEF values in patients with severe MR undergoing TEER.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS:<\/jats:title>\n            <jats:p>This multicenter registry study analyzed the associations between the predicted RVEF values and 1-year mortality in patients with severe MR undergoing TEER. To predict RVEF, 2-dimensional apical 4-chamber view videos from preprocedural transthoracic echocardiographic studies were exported and processed by a rigorously validated deep learning model.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS:<\/jats:title>\n            <jats:p>\n              Good-quality 2-dimensional apical 4-chamber view videos could be retrieved for 1154 patients undergoing TEER between 2017 and 2023. Survival at 1 year after TEER was 84.7%. The predicted RVEF values ranged from 26.6% to 64.0% and correlated only modestly with tricuspid annular plane systolic excursion (Pearson\n              <jats:italic>R<\/jats:italic>\n              =0.33;\n              <jats:italic>P<\/jats:italic>\n              &lt;0.001). Importantly, predicted RVEF was superior to tricuspid annular plane systolic excursion levels in predicting 1-year mortality after TEER (area under the curve, 0.687 versus 0.625;\n              <jats:italic>P<\/jats:italic>\n              =0.029). Furthermore, Kaplan-Meier survival analysis revealed that patients with reduced RV function (n=723; defined as a predicted RVEF of &lt;45%) had significantly worse 1-year survival rates than patients with preserved RV function (n=431; defined as a predicted RVEF of \u226545%; 80.3% [95% CI, 77.4%\u201383.3%] versus 92.1% [95% CI, 89.5%\u201394.7%]; hazard ratio for 1-year mortality, 2.67 [95% CI, 1.82\u20133.90];\n              <jats:italic>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>Deep learning\u2013enabled assessment of RV function using standard 2-dimensional echocardiographic videos can refine the prognostication of patients with severe MR undergoing TEER. Thus, it can be used to screen for patients with RV dysfunction who might benefit from intensified follow-up care.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/circimaging.124.017005","type":"journal-article","created":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T19:00:37Z","timestamp":1737486037000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":13,"title":["Deep Learning\u2013Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation"],"prefix":"10.1161","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1798-550X","authenticated-orcid":true,"given":"Mark","family":"Lachmann","sequence":"first","affiliation":[{"name":"First Department of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany (M.L., A.H., E.R., J.T., K.-L.L.)."},{"name":"DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance (M.L., A.H., E.R., M.v.S., A. Kastrati, H.S., M.J., E.X., K.-L.L., J.H., T.T.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vera","family":"Fortmeier","sequence":"additional","affiliation":[{"name":"Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum, Bad Oeynhausen, Germany (V.F., M.F., M.G., V.R.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1362-1493","authenticated-orcid":true,"given":"Lukas","family":"Stolz","sequence":"additional","affiliation":[{"name":"Medizinische Klinik und Poliklinik I, Klinikum der Universit\u00e4t M\u00fcnchen, Ludwig Maximilians University of Munich, Germany (L.S., J.H.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3036-4131","authenticated-orcid":true,"given":"M\u00e1rton","family":"Tokodi","sequence":"additional","affiliation":[{"name":"Heart and Vascular Center, Semmelweis University, Budapest, Hungary (M.T., A. Kov\u00e1cs)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2320-6434","authenticated-orcid":true,"given":"Attila","family":"Kov\u00e1cs","sequence":"additional","affiliation":[{"name":"Heart and Vascular Center, Semmelweis University, Budapest, Hungary (M.T., A. Kov\u00e1cs)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0535-9197","authenticated-orcid":true,"given":"Amelie","family":"Hesse","sequence":"additional","affiliation":[{"name":"First Department of Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany (M.L., A.H., E.R., J.T., K.-L.L.)."},{"name":"DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance (M.L., A.H., E.R., M.v.S., A. 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