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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
DC Field | Value | Language |
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dc.contributor.author | Lee, Taehee | - |
dc.contributor.author | Lee, Jeong Min | - |
dc.contributor.author | Yoon, Jeong Hee | - |
dc.contributor.author | Joo, Ijin | - |
dc.contributor.author | Bae, Jae Seok | - |
dc.contributor.author | Yoo, Jeongin | - |
dc.contributor.author | Kim, Jae Hyun | - |
dc.contributor.author | Ahn, Chulkyun | - |
dc.contributor.author | Kim, Jong Hyo | - |
dc.date.accessioned | 2022-09-30T05:54:22Z | - |
dc.date.available | 2022-09-30T05:54:22Z | - |
dc.date.created | 2022-08-26 | - |
dc.date.issued | 2022-09 | - |
dc.identifier.citation | European Radiology, Vol.32 No.9, pp.6407-6417 | - |
dc.identifier.issn | 0938-7994 | - |
dc.identifier.uri | https://hdl.handle.net/10371/184997 | - |
dc.description.abstract | Objectives 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.language | 영어 | - |
dc.publisher | Springer Verlag | - |
dc.title | Deep learning-based image reconstruction of 40-keV virtual monoenergetic images of dual-energy CT for the assessment of hypoenhancing hepatic metastasis | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s00330-022-08728-0 | - |
dc.citation.journaltitle | European Radiology | - |
dc.identifier.wosid | 000779772900006 | - |
dc.identifier.scopusid | 2-s2.0-85128271512 | - |
dc.citation.endpage | 6417 | - |
dc.citation.number | 9 | - |
dc.citation.startpage | 6407 | - |
dc.citation.volume | 32 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Lee, Jeong Min | - |
dc.contributor.affiliatedAuthor | Joo, Ijin | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
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