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Employing a 3D deep learning algorithm, the liver and spleen were automatically segmented from VNC images (derived from contrast-enhanced DECT scans) and true non-contrast (TNC) images, respectively. Mean volumetric CT attenuation values of each segmented liver (L) and spleen (S) were measured, allowing for liver attenuation index (LAI) calculation, defined as L minus S. Agreements of VNC and TNC parameters for hepatic steatosis, i.e., L and LAI, were assessed using intraclass correlation coefficients (ICC). Correlations between VNC parameters and MRI-PDFF values were assessed using the Pearson\u2019s correlation coefficient. Their performance to identify MRI-PDFF\u2009\u2265\u20095% and\u2009\u2265\u200910% was evaluated using receiver operating characteristic (ROC) curve analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 252 participants, 56 (22.2%) and 16 (6.3%) had hepatic steatosis with MRI-PDFF\u2009\u2265\u20095% and\u2009\u2265\u200910%, respectively. L\n                      <jats:sub>VNC<\/jats:sub>\n                      and LAI\n                      <jats:sub>VNC<\/jats:sub>\n                      showed excellent agreement with L\n                      <jats:sub>TNC<\/jats:sub>\n                      and LAI\n                      <jats:sub>TNC<\/jats:sub>\n                      (ICC\u2009=\u20090.957 and 0.968) and significant correlations with MRI-PDFF values (r\u2009=\u2009\u2212\u00a00.585 and \u2212\u00a00.588, Ps\u2009&lt;\u20090.001). L\n                      <jats:sub>VNC<\/jats:sub>\n                      and LAI\n                      <jats:sub>VNC<\/jats:sub>\n                      exhibited areas under the ROC curve of 0.795 and 0.806 for MRI-PDFF\u2009\u2265\u20095%; and 0.916 and 0.932, for MRI-PDFF\u2009\u2265\u200910%, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Volumetric CT attenuation-based parameters from VNC images generated by DECT, via automated 3D segmentation of the liver and spleen, have potential for opportunistic hepatic steatosis screening, as an alternative to TNC images.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11547-024-01833-8","type":"journal-article","created":{"date-parts":[[2024,6,13]],"date-time":"2024-06-13T02:01:56Z","timestamp":1718244116000},"page":"967-976","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Automated hepatic steatosis assessment on dual-energy CT-derived virtual non-contrast images through fully-automated 3D organ segmentation"],"prefix":"10.1007","volume":"129","author":[{"given":"Sun Kyung","family":"Jeon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1341-4072","authenticated-orcid":false,"given":"Ijin","family":"Joo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junghoan","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeongin","family":"Yoo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,6,13]]},"reference":[{"issue":"2","key":"1833_CR1","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1148\/radiol.2021204288","volume":"301","author":"J Starekova","year":"2021","unstructured":"Starekova J, Hernando D, Pickhardt PJ, Reeder SB (2021) Quantification of liver fat content with CT and MRI: state of the art. 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This retrospective study received approval from the institutional review board of Seoul National University Hospital, and the requirement for informed consent was waived due to the retrospective nature of this study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}