{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T15:50:08Z","timestamp":1791474608883,"version":"4.3.4"},"reference-count":52,"publisher":"Walter de Gruyter GmbH","issue":"4-5","license":[{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_bmt-2026-0247_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Ascending aortic growth in BAV varies widely, and baseline diameter insufficiently predicts individual risk; we assessed whether abnormal regional WSS surface burden relates to later AAo enlargement during longitudinal follow-up.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0247_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      The analysis included 37 patients with BAV and 66 healthy control subjects matched for age and sex. Baseline thoracic aortic phase-contrast\/4D-flow MRI was acquired using a 3.0-T Siemens MAGNETOM Skyra scanner to evaluate flow-related parameters across the aortic root, AAo, arch, and proximal descending thoracic aorta. The velocity-encoded 3D acquisition was planned to include the thoracic aorta, and axial or oblique axial source images were used for anatomical lo calization and AAo diameter measurement. Imaging parameters included TR 38.88\u202fms, TE 68.8\u202fms, flip angle 8\u00b0, matrix 256\u00a0\u00d7\u00a0256, field of view 300\u202fmm, spatial resolution 1.4\u00a0\u00d7\u00a01.4\u202fmm\n                      <jats:sup>2<\/jats:sup>\n                      , slice thickness 3\u202fmm, and interslice gap 0.6\u202fmm. Patient WSS maps were evaluated against healthy-control 95\u202f% confidence interval reference maps, and higher AAo growth was defined as annual enlargement greater than 0.25\u202fmm\/year.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0247_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>During 6.2-year median follow-up, higher-growth patients showed greater elevated AAo WSS area (20.6 vs. 6.0\u202f%; p=0.021).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0247_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Phase-contrast MRI-derived elevated WSS area may support individualized BAV surveillance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/bmt-2026-0247","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T04:56:57Z","timestamp":1784264217000},"page":"587-598","source":"Crossref","is-referenced-by-count":1,"title":["Phase-contrast MRI assessment of the thoracic aortic wall shear stress association with ascending aortic progression"],"prefix":"10.1515","volume":"71","author":[{"given":"Yuguang","family":"Ye","sequence":"first","affiliation":[{"name":"Faculty of Mathematics and Computer Science , Quanzhou Normal University , Quanzhou , China"},{"name":"Fujian Provincial Key Laboratory of Data Intensive Computing , Quanzhou , China"},{"name":"Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University , Quanzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taisheng","family":"Zeng","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science , Quanzhou Normal University , Quanzhou , China"},{"name":"Fujian Provincial Key Laboratory of Data Intensive Computing , Quanzhou , China"},{"name":"Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University , Quanzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yusi","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science , Quanzhou Normal University , Quanzhou , China"},{"name":"Fujian Provincial Key Laboratory of Data Intensive Computing , Quanzhou , China"},{"name":"Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University , Quanzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bijiao","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology , Huaqiao University Affiliated Strait Hospital , Quanzhou , Fujian , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifeng","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology , Huaqiao University Affiliated Strait Hospital , Quanzhou , Fujian , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianshe","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Diagnostic Radiology , Huaqiao University Affiliated Strait Hospital , Quanzhou , Fujian , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianlong","family":"Huang","sequence":"additional","affiliation":[{"name":"Faculty of Mathematics and Computer Science , Quanzhou Normal University , Quanzhou , China"},{"name":"Fujian Provincial Key Laboratory of Data Intensive Computing , Quanzhou , China"},{"name":"Key Laboratory of Intelligent Computing and Information Processing, Fujian Province University , Quanzhou , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"2026100814512982740_j_bmt-2026-0247_ref_001","doi-asserted-by":"crossref","unstructured":"Verma, S, Siu, SC. Bicuspid aortic valve disease. N\u00a0Engl J Med 2014;370:1920\u20139. https:\/\/doi.org\/10.1056\/NEJMra1207059.","DOI":"10.1056\/NEJMra1207059"},{"key":"2026100814512982740_j_bmt-2026-0247_ref_002","doi-asserted-by":"crossref","unstructured":"Ward, C. Clinical significance of the bicuspid aortic valve. Heart 2000;83:81\u20135. https:\/\/doi.org\/10.1136\/heart.83.1.81.","DOI":"10.1136\/heart.83.1.81"},{"key":"2026100814512982740_j_bmt-2026-0247_ref_003","doi-asserted-by":"crossref","unstructured":"Michelena, HI, Khanna, AD, Mahoney, D, Margaryan, E, Topilsky, Y, Suri, RM, et al.. Incidence of aortic complications in patients with bicuspid aortic valves. JAMA 2011;306:1104\u201312. https:\/\/doi.org\/10.1001\/jama.2011.1286.","DOI":"10.1001\/jama.2011.1286"},{"key":"2026100814512982740_j_bmt-2026-0247_ref_004","doi-asserted-by":"crossref","unstructured":"Tzemos, N, Therrien, J, Yip, J, Thanassoulis, G, Tremblay, S, Jamorski, MT, et al.. Outcomes in adults with bicuspid aortic valves. 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Arterioscler Thromb Vasc Biol 2020;40:e10\u201320. https:\/\/doi.org\/10.1161\/ATVBAHA.119.313636.","DOI":"10.1161\/ATVBAHA.120.314057"},{"key":"2026100814512982740_j_bmt-2026-0247_ref_038","doi-asserted-by":"crossref","unstructured":"Rahman, O, Scott, MB, Bollache, E, Suwa, K, Collins, JD, Carr, JC, et al.. Interval changes in aortic peak velocity and wall shear stress in patients with bicuspid aortic valve disease. Int J Cardiovasc Imag 2019;35:1925\u201334. https:\/\/doi.org\/10.1007\/s10554-019-01632-7.","DOI":"10.1007\/s10554-019-01632-7"},{"key":"2026100814512982740_j_bmt-2026-0247_ref_039","doi-asserted-by":"crossref","unstructured":"Sotelo, J, Dux-Santoy, L, Guala, A, Rodr\u00edguez-Palomares, JF, Evangelista, A, Sing-Long, C, et al.. 3D axial and circumferential wall shear stress from 4D flow MRI data using a finite element method and a Laplacian approach. 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