{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T13:13:52Z","timestamp":1783430032075,"version":"3.54.6"},"reference-count":36,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:00:00Z","timestamp":1775606400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004377","name":"Hong Kong Polytechnic University","doi-asserted-by":"publisher","award":["4\u2010W410"],"award-info":[{"award-number":["4\u2010W410"]}],"id":[{"id":"10.13039\/501100004377","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Liver International"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background &amp; Aims<\/jats:title>\n                    <jats:p>Transient elastography (TE) is routinely undertaken for non\u2010invasive assessment of liver fibrosis and steatosis, but is limited by its bulky design, inadequate imaging guidance and conventional algorithmic framework. Thus, we report a real\u2010time B\u2010mode image\u2013guided, artificial intelligence\u2013assisted, point\u2010of\u2010care TE (AI\u2010POC\u2010TE) system, providing simultaneous liver stiffness measurement (LSM) and a novel multi\u2010domain attenuation parameter (MAP) for fat quantification. We aimed to determine the accuracy of LSM and MAP in diagnosing histology\u2010confirmed fibrosis and steatosis in patients with chronic liver disease. Exploratory analyses assessed the minimum number of measurements required.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This prospective study included 138 patients who underwent liver biopsy and AI\u2010POC\u2010TE simultaneously, and diagnostic performance was evaluated by area under the receiver operating characteristic curve (AUROC). Another larger cohort of 1455 patients was examined to benchmark AI\u2010POC\u2010TE against conventional TE (Fibroscan).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      LSM by AI\u2010POC\u2010TE identified patients with fibrosis with AUROCs of 0.79 for \u2265F2, 0.79 for \u2265F3, 0.97 for F4. Corresponding Youden's cut\u2010offs were 8.2, 9.1 and 14.4\u2009kPa. MAP detected steatosis of \u2265\u2009S1, \u2265\u2009S2, S3 with AUROCs of 0.92, 0.70, 0.76 and Youden's cut\u2010offs were 244, 278 and 294\u2009dB\/m, respectively. Among 1455 patients using both TE techniques, liver stiffness was highly correlated (\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u20090.86) and MAP also correlated well with CAP (\n                      <jats:italic>r<\/jats:italic>\n                      \u2009=\u20090.80). Fewer than 10 measurements suffice to maintain accuracy; four measurements were statistically non\u2010inferior to the standard 10, supporting a streamlined protocol.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We found AI\u2010POC\u2010TE to accurately assess fibrosis and steatosis, comparable to conventional TE but with added values of portability, B\u2010mode guidance and deep learning\u2010based analytics.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/liv.70634","type":"journal-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T07:08:19Z","timestamp":1775632099000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of Hepatic Fibrosis and Steatosis via A Point\u2010of\u2010Care Transient Elastography System With Integrated\n                    <scp>AI<\/scp>"],"prefix":"10.1111","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8805-9773","authenticated-orcid":false,"given":"Zi\u2010Hao","family":"Huang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering The Hong Kong Polytechnic University  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen\u2010Hui","family":"Ye","sequence":"additional","affiliation":[{"name":"MAFLD Research Center, Department of Hepatology The First Affiliated Hospital of Wenzhou Medical University  Wenzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chong\u2010Lin","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering The Hong Kong Polytechnic University  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wan\u2010Rui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering 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