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Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics

Cited 6 time in Web of Science Cited 6 time in Scopus
Authors

Kim, Taek Min; Ahn, Hyungwoo; Lee, Hyo Jeong; Kim, Min Gwan; Cho, Jeong Yeon; Hwang, Sung Il; Kim, Sang Youn

Issue Date
2022-08
Publisher
Springer New York
Citation
Abdominal Radiology, Vol.47 No.8, pp.2867-2880
Abstract
Purpose This study aims to assess the computed tomography (CT) findings of renal epithelioid angiomyolipoma (EAML) and develop a radiomics-based model for differentiating EAMLs and clear cell renal cell carcinomas (RCCs). Method This two-center retrospective study included 28 histologically confirmed EAMLs and 56 size-matched clear cell RCCs with preoperative three-phase kidney CTs. We conducted subjective image analysis to determine the CT parameters that can distinguish EAMLs from clear cell RCCs. Training and test sets were divided by chronological order of CT scans, and radiomics model was built using ten selected features among radiomics and CT features. The diagnostic performance of the radiomics model was compared with that of the three radiologists using the area under the receiver-operating characteristic curve (AUC). Results The mean size of the EAMLs was 6.2 +/- 5.0 cm. On multivariate analysis, a snowman or ice cream cone tumor shape (OR 16.3; 95% CI 1.7-156.9, P = 0.02) and lower tumor-to-cortex (TOC) enhancement ratio in the corticomedullary phase (OR 33.4; 95% CI 5.7-197, P < 0.001) were significant independent factors for identifying EAMLs. The diagnostic performance of the radiomics model (AUC 0.89) was similar to those of genitourinary radiologists (AUC 0.78 and 0.81, P > 0.05) and superior to that of a third-year resident (AUC 0.63, P = 0.04). Conclusions A snowman or ice cream cone shape and lower TOC ratio were more closely associated with EAMLs than with clear cell RCCs. A CT radiomics model was useful for differentiating EAMLs from clear cell RCCs with better diagnostic performance than an inexperienced radiologist.
ISSN
2366-004X
URI
https://hdl.handle.net/10371/184577
DOI
https://doi.org/10.1007/s00261-022-03571-9
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