{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T04:25:32Z","timestamp":1786940732085,"version":"build-2736575974"},"reference-count":29,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,16]],"date-time":"2026-08-16T00:00:00Z","timestamp":1786838400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,16]],"date-time":"2026-08-16T00:00:00Z","timestamp":1786838400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF\u20102022R1F1A1071409"],"award-info":[{"award-number":["NRF\u20102022R1F1A1071409"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n Deep learning reconstruction can shorten breath\u2010hold MRI for liver proton density fat fraction (DL\u2010PDFF), but agreement with conventional PDFF (Conv\u2010PDFF) and the impact of measurement approach (regional vs. whole\u2010liver segmentation) remain unclear.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n To evaluate linearity and agreement of DL\u2010PDFF with Conv\u2010PDFF and MR spectroscopy PDFF (MRS\u2010PDFF), and reconstruction\u2010dependent whole\u2010liver distribution metrics.<\/jats:p>\n <\/jats:sec>\n \n Study Type<\/jats:title>\n Retrospective.<\/jats:p>\n <\/jats:sec>\n \n Population<\/jats:title>\n Fat phantom three vials per nominal fat mass fraction (27.86%, 18.32%, and 9.12%); 96 adults (53 males; median age, 64).<\/jats:p>\n <\/jats:sec>\n \n Field Strength\/Sequence<\/jats:title>\n 3\u2009T; Chemical shift\u2010encoded multi\u2010echo gradient\u2010echo; acquisition time, 10\u2009s (DL\u2010PDFF; acceleration factor [AF], 6) and 14\u2009s (Conv\u2010PDFF; AF, 4).<\/jats:p>\n <\/jats:sec>\n \n Assessment<\/jats:title>\n Central region of interest (ROI) for phantom PDFF; In\u00a0vivo, single ROI by radiology technologists, multiple ROIs by a resident and a medical student, and automated whole\u2010liver segmentation, yielding voxel\u2010based histograms and residual fitting error; inter\u2010observer agreement.<\/jats:p>\n <\/jats:sec>\n \n Statistical Tests<\/jats:title>\n \n Wilcoxon signed\u2010rank tests, linear regression (slope\/intercept\/\n R<\/jats:italic>\n 2<\/jats:sup>\n ), Bland\u2013Altman bias and 95% limits of agreement (LoA) with proportional\u2010bias slope (\n \u03b2<\/jats:italic>\n ), Lin's concordance correlation coefficient (CCC), Hodges\u2013Lehmann method, and Spearman (\n \u03c1<\/jats:italic>\n ). Two\u2010sided\n p<\/jats:italic>\n \u2009<\u20090.05.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n DL\u2010PDFF versus Conv\u2010PDFF showed excellent phantom linearity (\n R<\/jats:italic>\n 2<\/jats:sup>\n \u2009=\u20091.00). In patients, within the same approach: single ROI (bias, \u22120.24%; widest LoA, \u22122.76 to 2.28; CCC, 0.94); multiple ROIs (bias, \u22120.002; LoA, \u22121.04 to 1.04; CCC, 0.99); and whole\u2010liver segmentation (bias, 0.12; LoA, \u22120.54 to 0.78; CCC, 0.99). Cross\u2010method comparison (DL\u2010PDFF segmentation vs. Conv\u2010PDFF multiple ROIs) showed larger bias (0.57; LoA, \u22120.77 to 1.91; CCC, 0.97). Against MRS\u2010PDFF, bias was similar (\u22120.05 to \u22120.02; LoA, \u22123.00 to 2.96). For DL\u2010PDFF, whole\u2010liver SD (Hodges\u2013Lehmann difference, 0.55%;\n \u03c1<\/jats:italic>\n \u2009=\u20090.95) and residual fitting error significantly higher (median, 2.80 vs. 1.92). Inter\u2010observer agreement was high (CCC, 0.99).\n <\/jats:p>\n <\/jats:sec>\n \n Data Conclusion<\/jats:title>\n DL\u2010PDFF demonstrated high agreement with Conv\u2010PDFF while reducing acquisition time. However, measurement approach (segmentation vs. ROI) contributes larger systematic differences relevant to longitudinal and cross\u2010study comparisons.<\/jats:p>\n <\/jats:sec>\n \n Evidence Level<\/jats:title>\n 3.<\/jats:p>\n <\/jats:sec>\n \n Stage of Technical Efficacy<\/jats:title>\n 2.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jmri.70511","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T04:06:00Z","timestamp":1786939560000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning\u2010Accelerated\n MRI<\/scp>\n Assessment of Hepatic Proton Density Fat Fraction: Agreement With Conventional Acquisition Across Manual and Automated Measurement Approaches"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7692-3413","authenticated-orcid":false,"given":"Seo Yeon","family":"Youn","sequence":"first","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bohyun","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0197-8460","authenticated-orcid":false,"given":"Hyun\u2010Soo","family":"Lee","sequence":"additional","affiliation":[{"name":"Siemens Healthineers, Ltd. Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jungwoo","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2094-0061","authenticated-orcid":false,"given":"Seohyun","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Medicine College of Medicine, Gachon University Incheon Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0360-7233","authenticated-orcid":false,"given":"Dominik","family":"Nickel","sequence":"additional","affiliation":[{"name":"Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG Erlangen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabine","family":"Mollus","sequence":"additional","affiliation":[{"name":"Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG Erlangen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan","family":"Kannengiesser","sequence":"additional","affiliation":[{"name":"Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG Erlangen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0018-8712","authenticated-orcid":false,"given":"Joon\u2010Il","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5695-4426","authenticated-orcid":false,"given":"Yu Ri","family":"Shin","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2373-7024","authenticated-orcid":false,"given":"Soon Nam","family":"Oh","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1514-929X","authenticated-orcid":false,"given":"Sung Eun","family":"Rha","sequence":"additional","affiliation":[{"name":"Department of Radiology Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea Seoul Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,16]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhep.2023.06.003"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMra011775"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/jgh.12271"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.14309\/ctg.0000000000000081"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/hep.29639"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2017170550"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26575"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2021204288"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.29750"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2025.112641"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1088\/1681\u20107575\/ad1f7f"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330\u2010024\u201010693\u20109"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000825"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12102370"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.17.17812"},{"key":"e_1_2_8_17_1","first-page":"130","article-title":"Multiscale Vessel Enhancement Filtering","volume":"1496","author":"Frangi A.","year":"2000","journal-title":"Medical Image Computing and Computer Assisted Intervention"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25880"},{"key":"e_1_2_8_19_1","unstructured":"Q. 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