{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T13:27:55Z","timestamp":1791379675106,"version":"4.3.3"},"reference-count":40,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Liver International"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background &amp; Aims<\/jats:title>\n                    <jats:p>There is an unmet need for a reliable and reproducible non\u2010invasive measure of fatty liver content (FLC) for monitoring steatotic liver disease in clinical practice. Sonographic FLC assessment is qualitative and operator\u2010dependent, and the dynamic quantification range of algorithms based on a single ultrasound (US) parameter is unsatisfactory.<\/jats:p>\n                    <jats:p>This study aims to develop and validate a new multiparametric algorithm based on B\u2010mode images to quantify FLC using Magnetic Resonance (MR) values as standard reference.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Patients with elevated liver enzymes and\/or bright liver at US (\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u2009195) underwent FLC evaluation by MR and by US. Five US\u2010derived quantitative features [attenuation rate(AR), hepatic renal\u2010ratio(HR), diaphragm visualization(DV), hepatic\u2010portal\u2010vein\u2010ratio(HPV), portal\u2010vein\u2010wall(PVW)] were combined by mixed linear\/exponential regression in a multiparametric model (Steatoscore2.0). One hundred and thirty\u2010four subjects were used for training and 61 for independent validations; score\u2010computation underwent an inter\u2010operator reproducibility analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The model is based on a mixed linear\/exponential combination of 3 US parameters (AR, HR, DV), modelled by 2 equations according to AR values. The computation of FLC by Steatoscore2.0 (mean\u2009\u00b1\u2009std, 7.91%\u2009\u00b1\u20098.69) and MR (mean\u2009\u00b1\u2009std, 8.10%\u2009\u00b1\u200910.31) is highly correlated with a low root mean square error in both training\/validation cohorts, respectively (\n                      <jats:italic>R<\/jats:italic>\n                      \u2009=\u20090.92\/0.86 and RMSE\u2009=\u20095.15\/4.62,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u2009.001). Steatoscore2.0 identified patients with MR\u2010FLC\u22655%\/\u226510% with sensitivity\u2009=\u200993.2%\/89.4%, specificity\u2009=\u200986.1%\/95.8%, AUROC\u2009=\u20090.958\/0.975, respectively and correlated with MR (\n                      <jats:italic>R<\/jats:italic>\n                      \u2009=\u20090.92) significantly (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u2009.001) better than CAP (\n                      <jats:italic>R<\/jats:italic>\n                      \u2009=\u20090.73).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Multiparametric Steatoscore2.0 measures FLC providing values highly comparable with MR. It is reliable, inexpensive, easy to use with any US equipment and qualifies to be tested in larger, prospective studies as new tool for the non\u2010invasive screening and monitoring of FLC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/liv.16078","type":"journal-article","created":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T07:55:02Z","timestamp":1724745302000},"page":"3008-3019","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["An ultrasound multiparametric method to quantify liver fat using magnetic resonance as standard reference"],"prefix":"10.1111","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6030-8483","authenticated-orcid":false,"given":"Laura","family":"De\u00a0Rosa","sequence":"first","affiliation":[{"name":"Institute of Clinical Physiology National Research Council  Pisa Italy"},{"name":"Department of Information Engineering and Computer Science University of 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