{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T13:29:25Z","timestamp":1788355765277,"version":"build-2803163510"},"reference-count":12,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,6,12]],"date-time":"2024-06-12T00:00:00Z","timestamp":1718150400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health Welfare, the Ministry of Food and Drug Safety","award":["RS-2020-KD000007"],"award-info":[{"award-number":["RS-2020-KD000007"]}]},{"name":"Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health Welfare, the Ministry of Food and Drug Safety","award":["16-2020-0001"],"award-info":[{"award-number":["16-2020-0001"]}]},{"name":"SNUBH Research Fund","award":["RS-2020-KD000007"],"award-info":[{"award-number":["RS-2020-KD000007"]}]},{"name":"SNUBH Research Fund","award":["16-2020-0001"],"award-info":[{"award-number":["16-2020-0001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Non-alcoholic fatty liver disease (NAFLD), prevalent among conditions like obesity and diabetes, is globally significant. Existing ultrasound diagnosis methods, despite their use, often lack accuracy and precision, necessitating innovative solutions like AI. This study aims to validate an AI-enhanced quantitative ultrasound (QUS) algorithm for NAFLD severity assessment and compare its performance with Magnetic Resonance Imaging Proton Density Fat Fraction (MRI-PDFF), a conventional diagnostic tool. A single-center cross-sectional pilot study was conducted. Liver fat content was estimated using an AI-enhanced quantitative ultrasound attenuation coefficient (QUS-AC) of Barreleye Inc. with an AI-based QUS algorithm and two conventional ultrasound techniques, FibroTouch Ultrasound Attenuation Parameter (UAP) and Canon Attenuation Imaging (ATI). The results were compared with MRI-PDFF values. The intraclass correlation coefficient (ICC) was also assessed. Significant correlation was found between the QUS-AC and the MRI-PDFF, reflected by an R value of 0.95. On other hand, ATI and UAP displayed lower correlations with MRI-PDFF, yielding R values of 0.73 and 0.51, respectively. In addition, ICC for QUS-AC was 0.983 for individual observations. On the other hand, the ICCs for ATI and UAP were 0.76 and 0.39, respectively. Our findings suggest that AC with AI-enhanced QUS could serve as a valuable tool for the non-invasive diagnosis of NAFLD.<\/jats:p>","DOI":"10.3390\/diagnostics14121237","type":"journal-article","created":{"date-parts":[[2024,6,13]],"date-time":"2024-06-13T04:30:12Z","timestamp":1718253012000},"page":"1237","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Application of Quantitative Ultrasonography and Artificial Intelligence for Assessing Severity of Fatty Liver: A Pilot Study"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0960-0198","authenticated-orcid":false,"given":"Hyuksool","family":"Kwon","sequence":"first","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea"},{"name":"Imaging Division, Department of Emergency Medicine, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7269-3959","authenticated-orcid":false,"given":"Myeong-Gee","family":"Kim","sequence":"additional","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SeokHwan","family":"Oh","sequence":"additional","affiliation":[{"name":"Laboratory of Quantitative Ultrasound Imaging, Seoul National University Bundang Hospital, Seong-nam 13620, Republic of Korea"},{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youngmin","family":"Kim","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guil","family":"Jung","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeon-Jik","family":"Lee","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang-Yun","family":"Kim","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeon-Min","family":"Bae","sequence":"additional","affiliation":[{"name":"Barreleye Inc., 312, Teheran-ro, Gangnam-gu, Seoul 06221, Republic of Korea"},{"name":"Electrical Engineering Department, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.cmet.2023.02.003","article-title":"The global burden of metabolic disease: Data from 2000 to 2019","volume":"35","author":"Chew","year":"2023","journal-title":"Cell Metab."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1038\/s41575-021-00523-4","article-title":"Advancing the global public health agenda for NAFLD: A consensus statement","volume":"19","author":"Lazarus","year":"2021","journal-title":"Nat. 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