{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T03:42:56Z","timestamp":1788925376818,"version":"build-2803163510"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"vor","delay-in-days":65,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Development and Transformation of New Technology"},{"name":"Construction of Precision Diagnosis and Treatment System for Transcatheter Interventional Diagnosis"},{"name":"Treatment of Structural Heart Diseases","award":["2022YFC2503400"],"award-info":[{"award-number":["2022YFC2503400"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation","doi-asserted-by":"publisher","award":["82370375"],"award-info":[{"award-number":["82370375"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Research on Key Techniques of Minimally Invasive Treatment for Valvular Heart Diseases","award":["2023-YBSF-105"],"award-info":[{"award-number":["2023-YBSF-105"]}]},{"name":"Xijing Hospital Booster Foundation","award":["XJZT24LY42"],"award-info":[{"award-number":["XJZT24LY42"]}]},{"DOI":"10.13039\/501100000287","name":"Royal Academy of Engineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000287","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RAEng Chair in Emerging Technologies","award":["INSILEX CiET1919\/19"],"award-info":[{"award-number":["INSILEX CiET1919\/19"]}]},{"name":"ERC Advanced Grant"},{"name":"UKRI Frontier Research Guarantee","award":["INSILICO EP\/Y030494\/1"],"award-info":[{"award-number":["INSILICO EP\/Y030494\/1"]}]},{"name":"UK Centre of Excellence on in-silico Regulatory Science and Innovation","award":["10139527"],"award-info":[{"award-number":["10139527"]}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health and Care Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014653","name":"Manchester Biomedical Research Centre","doi-asserted-by":"publisher","award":["NIHR203308"],"award-info":[{"award-number":["NIHR203308"]}],"id":[{"id":"10.13039\/100014653","id-type":"DOI","asserted-by":"publisher"}]},{"name":"BHF Manchester Centre of Research Excellence","award":["RE\/24\/130017"],"award-info":[{"award-number":["RE\/24\/130017"]}]},{"name":"Peixin Medical Co. Ltd"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Bicuspid aortic valve (BAV) stenosis complicates transcatheter aortic valve replacement (TAVR) planning, with no validated automated measurement algorithm available. We developed Cardioverse, the first fully automated deep learning algorithm for BAV anatomical assessment in TAVR planning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>We conducted a large-scale, multicenter retrospective study encompassing 1,147 consecutive patients with BAV undergoing TAVR across 16 high-volume Chinese centers (March 2019\u2013February 2023). Cardioverse was trained on this cohort and evaluated in an internal (n = 437) and external (n = 110) validation cohorts. Our novel Cardioverse algorithm demonstrated exceptional segmentation performance across all anatomical targets with Dice similarity coefficients &amp;gt;0.97 for coronary cusps and ostia. Critically, the algorithm achieved unprecedented workflow efficiency gains: 80% reduction in assessment time [241.0 IQR (181.0, 297.0) vs. 1251.0 IQR (872.0, 1408.0) seconds], 85% reduction in user interactions [57.0 IQR (45.0, 78.0) vs. 382.5 IQR (285.5, 475.0) clicks], and 87% reduction in manual effort [7.5 IQR (4.8, 9.3) vs. 57.2 IQR (43.5, 68.4) meters mouse movement] compared to expert observers (P &amp;lt; 0.001). Importantly, accuracy was maintained across all BAV phenotypes with correlation coefficients &amp;gt;0.91 for all critical measurements, including annular dimensions, calcification quantification, and aortic root morphology assessment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Cardioverse transforms pre-TAVR assessment for BAV patients, offering a validated solution combining accuracy and efficiency. It reduces assessment time from over 20 min to &amp;lt; 5 min, addressing the need for standardized, rapid, and reliable BAV evaluation. Its robust performance across diverse BAV phenotypes makes it a crucial tool for enhancing TAVR planning consistency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical trial registration<\/jats:title>\n                    <jats:p>ClinicalTrials.gov Protocol Registration System (NCT05044338).<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjimp\/qyaf153","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T13:16:04Z","timestamp":1764854164000},"source":"Crossref","is-referenced-by-count":1,"title":["Precision TAVR quantification\u2014 AI-accelerated TAVR planning reduces assessment time by 80% in bicuspid aortic stenosis"],"prefix":"10.1093","volume":"3","author":[{"given":"Yu","family":"Mao","sequence":"first","affiliation":[{"name":"Department of Cardiovascular Surgery, Xijing Hospital Affiliated to Air Force Medical University , Xi\u2019an, Shaanxi ,","place":["China"]},{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University , Shanghai ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Xijing Hospital Affiliated to Air Force Medical University , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengen","family":"Zhai","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Xijing Hospital Affiliated to Air Force Medical University , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Xijing Hospital Affiliated to Air Force Medical University , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjing","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Clinical Research, MAKE medical Technology Co. Ltd. , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinglong","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Clinical Research, MAKE medical Technology Co. Ltd. , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangyao","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics, School of Public Health, Xi\u2019an Jiaotong University Health Science Center , Xi\u2019an, Shaanxi ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaodong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Research and Development, Suzhou Peixin Technology Co., Ltd. , Suzhou ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanchi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Medical Affairs, Peijia Medical Company Limited , Suzhou ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gejun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College , Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongxin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Shandong Qianfoshan Hospital , Jinan, Shandong ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8332-8508","authenticated-orcid":false,"given":"Yining","family":"Yang","sequence":"additional","affiliation":[{"name":"Heart Center, The First Affiliated Hospital of Xinjiang Medical University , Urumqi, Xinjiang Uygur Autonomous Region ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haibo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Anzhen Hospital, Capital Medical University , Beijing ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, Guangdong Provincial People\u2019s Hospital , Guangzhou, Guangdong ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingqiang","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Surgery, West China Hospital, Sichuan University , Chengdu, Sichuan ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5590-8396","authenticated-orcid":false,"given":"Yongjian","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College , Beijing 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