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Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis

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dc.contributor.authorLee, Taehee-
dc.contributor.authorLee, Jeong Min-
dc.contributor.authorYoon, Jeong Hee-
dc.contributor.authorJoo, Ijin-
dc.contributor.authorBae, Jae Seok-
dc.contributor.authorYoo, Jeongin-
dc.contributor.authorKim, Jae Hyun-
dc.contributor.authorAhn, Chulkyun-
dc.contributor.authorKim, Jong Hyo-
dc.date.accessioned2022-09-30T05:54:22Z-
dc.date.available2022-09-30T05:54:22Z-
dc.date.created2022-08-26-
dc.date.issued2022-09-
dc.identifier.citationEuropean Radiology, Vol.32 No.9, pp.6407-6417-
dc.identifier.issn0938-7994-
dc.identifier.urihttps://hdl.handle.net/10371/184997-
dc.description.abstractObjectives To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases. Methods This retrospective study included 131 patients who underwent contrast-enhanced DECT (80-kVp and 150-kVp with a tin filter) in the portal venous phase for hepatic metastasis surveillance. Linearly blended images simulating 100-kVp images (100-kVp), standard 40-keV VMI images (40-keV VMI), and post-processed 40-keV VMI using a vendor-agnostic DLM (i.e., DLM 40-keV VMI) were reconstructed. Lesion conspicuity and diagnostic acceptability were assessed by three independent reviewers and compared using the Wilcoxon signed-rank test. The contrast-to-noise ratios (CNRs) were also measured placing ROIs in metastatic lesions and liver parenchyma. The detection performance of hepatic metastases was assessed by using a jackknife alternative free-response ROC method. The consensus by two independent radiologists was used as the reference standard. Results DLM 40-keV VMI, compared to 40-keV VMI and 100-kVp, showed a higher lesion-to-liver CNR (8.25 +/- 3.23 vs. 6.05 +/- 2.38 vs. 5.99 +/- 2.00), better lesion conspicuity (4.3 (4.0-4.7) vs. 3.7 (3.7-4.0) vs. 3.7 (3.3-4.0)), and better diagnostic acceptability (4.3 (4.0-4.3) vs. 3.0 (2.7-3.3) vs. 4.0 (4.0-4.3)) (p < 0.001 for all). For lesion detection (246 hepatic metastases in 68 patients), the figure of merit was significantly higher with DLM 40-keV VMI than with 40-keV VMI (0.852 vs. 0.822, p = 0.012), whereas no significant difference existed between DLM 40-keV VMI and 100-kVp (0.852 vs. 0.842, p = 0.31). Conclusions DLM 40-keV VMI provided better image quality and comparable diagnostic performance for detecting hypoenhancing hepatic metastases compared to linearly blended images.-
dc.language영어-
dc.publisherSpringer Verlag-
dc.titleDeep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis-
dc.typeArticle-
dc.identifier.doi10.1007/s00330-022-08728-0-
dc.citation.journaltitleEuropean Radiology-
dc.identifier.wosid000779772900006-
dc.identifier.scopusid2-s2.0-85128271512-
dc.citation.endpage6417-
dc.citation.number9-
dc.citation.startpage6407-
dc.citation.volume32-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Jeong Min-
dc.contributor.affiliatedAuthorJoo, Ijin-
dc.type.docTypeArticle-
dc.description.journalClass1-
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