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A radiomics nomogram for predicting transcatheter arterial chemoembolization refractoriness of hepatocellular carcinoma without extrahepatic metastasis or macrovascular invasion

Title
A radiomics nomogram for predicting transcatheter arterial chemoembolization refractoriness of hepatocellular carcinoma without extrahepatic metastasis or macrovascular invasion
Authors
Sheen, HeesoonKim, Jin SilLee, Jeong KyongChoi, Sun YoungBaek, Seung YonKim, Jung Young
Ewha Authors
백승연이정경최선영김진실
SCOPUS Author ID
백승연scopus; 이정경scopus; 최선영scopusscopus; 김진실scopus
Issue Date
2021
Journal Title
ABDOMINAL RADIOLOGY
ISSN
2366-004XJCR Link

2366-0058JCR Link
Citation
ABDOMINAL RADIOLOGY vol. 46, no. 6, pp. 2839 - 2849
Keywords
Hepatocellular carcinomaTransarterial chemoembolizationRefractorinessRadiomicsNomogram
Publisher
SPRINGER
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Objective A radiomics nomogram for pretreatment prediction of TACE refractoriness was developed and validated for hepatocellular carcinoma (HCC) without extrahepatic metastasis or macrovascular invasion. Materials and methods This study included 80 patients with HCC without extrahepatic metastasis or macrovascular involvement treated with TACE between July 2016 and November 2018. The datasets were divided into a training set (80%) and a test set (20%) for feature selection and tenfold cross-validation. Forty radiomic features were extracted from arterial-phase computed tomography (CT) using the Local Image Features Extraction software. The Lasso regression model was used for radiomics signature selection. The Lasso regression model was used for radiomics signature selection and the selected signatures were validated using the Mann-Whitney U-test. The radiomics nomogram was developed based on a multivariate logistic regression model incorporating the Rad-score, CT imaging factors, and clinical factors, and it was validated. Results The Rad-score, which consists of the Gray-Level Zone Length Matrix (GLZLM)-Long-Zone Low Gray-Level Emphasis (LZLGE) and GLZLM-Gray-Level Non-Uniformity (GLNU), T-stage, log alpha-fetoprotein (AFP), and bilobar distribution were significantly associated with TACE refractoriness (p < 0.05). Predictors in the radiomics nomogram were the Rad-score and T-stage (Rad-score + T-stage), Rad-score and bilobar distribution (Rad-score + bilobar distribution), or Rad-score and logAFP (Rad-score + logAFP). The multivariate logistic regression model showed a good predictive performance (Rad-score + T-stage, AUC, 0.95; Rad-score + bilobar distribution, AUC 0.91; and Rad-score + logAFP, AUC, 0.91). Conclusion The radiomics nomogram could be used for the pretreatment prediction of TACE refractoriness.
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DOI
10.1007/s00261-020-02884-x
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의과대학 > 의학과 > Journal papers
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