Utilizing fully-automated 3D organ segmentation for hepatic steatosis assessment with CT attenuation-based parameters

被引:4
|
作者
Yoo, Jeongin [1 ]
Joo, Ijin [1 ,2 ,3 ]
Jeon, Sun Kyung [1 ]
Park, Junghoan [1 ]
Yoon, Soon Ho [1 ,2 ,4 ]
机构
[1] Seoul Natl Univ Hosp, Dept Radiol, 101 Daehak Ro,Jongno Gu, Seoul 03080, South Korea
[2] Seoul Natl Univ, Coll Med, Dept Radiol, 103 Daehak Ro,Jongno Gu, Seoul 03080, South Korea
[3] Seoul Natl Univ, Seoul Natl Univ Hosp, Inst Radiat Med, Med Res Ctr, 101 Daehak Ro,Jongno Gu, Seoul 03080, South Korea
[4] MEDICALIP Co Ltd, Seoul, South Korea
关键词
Fatty liver; Non-alcoholic fatty liver disease; Deep learning; Multidetector computed tomography; FATTY LIVER-DISEASE; COMPUTED-TOMOGRAPHY; QUANTIFICATION; DIAGNOSIS; DONORS; MRI;
D O I
10.1007/s00330-024-10660-4
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesTo investigate the clinical utility of fully-automated 3D organ segmentation in assessing hepatic steatosis on pre-contrast and post-contrast CT images using magnetic resonance spectroscopy (MRS)-proton density fat fraction (PDFF) as reference standard.Materials and methodsThis retrospective study analyzed 362 adult potential living liver donors with abdominal CT scans and MRS-PDFF. Using a deep learning-based tool, mean volumetric CT attenuation of the liver and spleen were measured on pre-contrast (liver(L)_pre and spleen(S)_pre) and post-contrast (L_post and S_post) images. Agreements between volumetric and manual region-of-interest (ROI)-based measurements were assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Diagnostic performances of volumetric parameters (L_pre, liver-minus-spleen (L-S)_pre, L_post, and L-S_post) were evaluated for detecting MRS-PDFF >= 5% and >= 10% using receiver operating characteristic (ROC) curve analysis and compared with those of ROI-based parameters.ResultsAmong the 362 subjects, 105 and 35 had hepatic steatosis with MRS-PDFF >= 5% and >= 10%, respectively. Volumetric and ROI-based measurements revealed ICCs of 0.974, 0.825, 0.992, and 0.962, with mean differences of -4.2 HU, -3.4 HU, -1.2 HU, and -7.7 HU for L_pre, S_pre, L_post, and S_post, respectively. Volumetric L_pre, L-S_pre, L_post, and L-S_post yielded areas under the ROC curve of 0.813, 0.813, 0.734, and 0.817 for MRS-PDFF >= 5%; and 0.901, 0.915, 0.818, and 0.868 for MRS-PDFF >= 10%, comparable with those of ROI-based parameters (0.735-0.818; and 0.816-0.895, Ps = 0.228-0.911).ConclusionAutomated 3D segmentation of the liver and spleen in CT scans can provide volumetric CT attenuation-based parameters to detect and grade hepatic steatosis, applicable to pre-contrast and post-contrast images.Clinical relevance statementVolumetric CT attenuation-based parameters of the liver and spleen, obtained through automated segmentation tools from pre-contrast or post-contrast CT scans, can efficiently detect and grade hepatic steatosis, making them applicable for large population data collection.Key Points center dot Automated organ segmentation enables the extraction of CT attenuation-based parameters for the target organ.center dot Volumetric liver and spleen CT attenuation-based parameters are highly accurate in hepatic steatosis assessment.center dot Automated CT measurements from pre- or post-contrast imaging show promise for hepatic steatosis screening in large cohorts.Key Points center dot Automated organ segmentation enables the extraction of CT attenuation-based parameters for the target organ.center dot Volumetric liver and spleen CT attenuation-based parameters are highly accurate in hepatic steatosis assessment.center dot Automated CT measurements from pre- or post-contrast imaging show promise for hepatic steatosis screening in large cohorts.Key Points center dot Automated organ segmentation enables the extraction of CT attenuation-based parameters for the target organ.center dot Volumetric liver and spleen CT attenuation-based parameters are highly accurate in hepatic steatosis assessment.center dot Automated CT measurements from pre- or post-contrast imaging show promise for hepatic steatosis screening in large cohorts.
引用
收藏
页码:6205 / 6213
页数:9
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