{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:04:11Z","timestamp":1770912251337,"version":"3.50.1"},"reference-count":24,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFC2410701"],"award-info":[{"award-number":["2023YFC2410701"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023A151503016"],"award-info":[{"award-number":["2023A151503016"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62301550"],"award-info":[{"award-number":["62301550"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To establish and validate an online model fitting\u2010based flip angle calculation method for flip angle modulated (FAM) chemical shift\u2010encoded (CSE) MRI integrated with simultaneous multi\u2010slice (SMS) imaging for achieving fast and accurate abdominal proton\u2010density fat fraction (PDFF) and R2* quantification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Gaussian functions were fitted to directly determine optimal FA profiles, thereby avoiding computationally intensive iterative optimization. Inter\u2010slice SMS acceleration was incorporated to improve acquisition efficiency. Fat\u2010water phantom and volunteer with varying liver fat deposition were scanned at 3.0\u2009T to validate the accuracy of PDFF and R2* quantification across different PE steps with different acceleration methods by inter\u2010slice SMS (FAM\u2010SMS), in\u2010plane GRAPPA (FAM\u2010GRAPPA), and combination of SMS and GRAPPA (FAM\u2010Hybrid), using low\u2010FA 3D acquisitions as reference. Relative noise level (rNL) was defined to evaluate the acquisition efficiency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In the phantom study (PDFF: 6.2%\u201335.7%; R2*: 29.2\u2013154.3\u2009s\n                      <jats:sup>\u22121<\/jats:sup>\n                      ), the model\u2010fitted FA profiles closely matched optimized profiles, showing unbiased PDFF and R2* (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&gt;\u20090.05). FAM\u2010SMS showed high correlation with 3D reference (PDFF: 0.994\u20130.995, R2*: 0.978\u20130.988). In vivo study, FAM\u2010SMS achieved comparable noise levels to 3D acquisition (PDFF: 0.9%\u201328.7%; R2*: 32.7\u201385.4\u2009s\n                      <jats:sup>\u22121<\/jats:sup>\n                      ), demonstrating 18.7% lower PDFF SD and 18.5% lower R2* SD compared to FAM\u2010GRAPPA (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05). Despite higher SD, FAM\u2010Hybrid reduced rNL by 8.0% (PDFF) and 17.0% (R2*) versus FAM\u2010GRAPPA.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed 2D FAM method with model\u2010fitted FA calculation and SMS acceleration provides fast, accurate, and motion\u2010robust liver PDFF and R2* imaging, with superior noise performance to GRAPPA, enabling simplified protocol design.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70197","type":"journal-article","created":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T04:26:16Z","timestamp":1764044776000},"page":"2223-2231","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fast and Accurate Abdominal\n                    <scp>PDFF<\/scp>\n                    and\n                    <scp>R2<\/scp>\n                    * Mapping With Model\u2010Fitted Flip Angle Modulation and Simultaneous Multi\u2010Slice (\n                    <scp>SMS<\/scp>\n                    )\n                    <scp>2D<\/scp>\n                    Imaging"],"prefix":"10.1002","volume":"95","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5709-9799","authenticated-orcid":false,"given":"Chuanli","family":"Cheng","sequence":"first","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liwen","family":"Wan","sequence":"additional","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6279-9514","authenticated-orcid":false,"given":"Hao","family":"Peng","sequence":"additional","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Wan","sequence":"additional","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1358-9777","authenticated-orcid":false,"given":"Dong","family":"Liang","sequence":"additional","affiliation":[{"name":"Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences  Shenzhen China"},{"name":"State Key Laboratory of Biomedical Imaging Science and System  Shenzhen China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8558-5102","authenticated-orcid":false,"given":"Hairong","family":"Zheng","sequence":"additional","affiliation":[{"name":"Paul C. 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