{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T21:57:25Z","timestamp":1778795845221,"version":"3.51.4"},"reference-count":29,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82471948"],"award-info":[{"award-number":["82471948"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82271958"],"award-info":[{"award-number":["82271958"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2024A1515012149"],"award-info":[{"award-number":["2024A1515012149"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Liver International"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>The diagnostic performance of the Liver Imaging Reporting and Data System (LI\u2010RADS) version 2018 (v2018), its modifications modified LI\u2010RADS (mLI\u2010RADS) and revised LI\u2010RADS (rLI\u2010RADS), for diagnosing hepatocellular carcinoma (HCC) remains poorly understood and requires further validation. This multicentre study aimed to evaluate the diagnostic performance of three algorithms in diagnosing HCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We included 1092 untreated patients at risk for developing HCC who underwent gadoxetic acid\u2013enhanced MRI across three independent cohorts from January 2020 to December 2022. Two readers independently interpreted each hepatic lesion and recorded their imaging features. The readers' judgements regarding whether the lesion was HCC or not were also noted. Non\u2010HCC cases were confirmed based on histologic and clinical follow\u2010up data, while HCC cases were pathologically confirmed. Diagnostic performance metrics were compared using bootstrap resampling and generalised estimating equations. Additionally, the diagnostic odds ratio (DOR) was evaluated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 1313 lesions, 52.3% (687\/1313) were diagnosed as HCC. For all hepatic lesions, mLI\u2010RADS achieved higher sensitivity (82.9%) and accuracy (84.1%) than LI\u2010RADS v2018 (sensitivity, 79.9%,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.024; accuracy, 83.2%) and rLI\u2010RADS (sensitivity, 81.3%; accuracy, 83.8%), while maintaining a similar positive predictive value (mLI\u2010RADS, 86.2%; LI\u2010RADS v2018, 86.9%; rLI\u2010RADS, 86.9%). The DORs were 28.3 (95% CI: 21.1\u201338.0) for mLI\u2010RADS, 27.8 (95% CI: 20.6\u201337.7) for LI\u2010RADS v2018 and 26.0 (95% CI: 19.3\u201335.0) for rLI\u2010RADS. The readers' judgement exhibited higher accuracy than that of three algorithms (87.7%: 83.2%\u201384.1%).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>For the diagnosis of HCC in an HBV\u2010predominant cohort, mLI\u2010RADS showed higher performance compared with LI\u2010RADS v2018 and rLI\u2010RADS. Reader judgement achieved higher accuracy than all algorithms, highlighting the role of clinical expertise.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>NCT06663904<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/liv.70366","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T17:30:11Z","timestamp":1759512611000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Diagnosis of Hepatocellular Carcinoma Using Gadoxetic Acid\u2010Enhanced\n                    <scp>MRI<\/scp>\n                    Based on\n                    <scp>LI<\/scp>\n                    \u2010\n                    <scp>RADS<\/scp>\n                    Version 2018 and\n                    <scp>LI<\/scp>\n                    \u2010\n                    <scp>RADS<\/scp>\n                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University  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhoukun","family":"Ling","sequence":"additional","affiliation":[{"name":"Department of Radiology Guangzhou Eighth People's Hospital, Guangzhou Medical University  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lujie","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital, Sun Yat\u2010Sen University  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaochu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital, Sun Yat\u2010Sen University  Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital, Sun Yat\u2010Sen University  Guangzhou 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