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A predictive model of incomplete response after transarterial chemoembolization for early or intermediate stage of hepatocellular carcinoma: consideration of hepatic angiographic and cross-sectional imaging.
Tao, Pei-Yao; Zhang, Zi-Shu; Wang, Tian-Cheng; Yu, Meng-Qi; Xiao, Yu-Dong.
Afiliación
  • Tao PY; Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139 Middle Renmin Road, Changsha, 410011, China.
  • Zhang ZS; Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139 Middle Renmin Road, Changsha, 410011, China.
  • Wang TC; Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139 Middle Renmin Road, Changsha, 410011, China.
  • Yu MQ; Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139 Middle Renmin Road, Changsha, 410011, China.
  • Xiao YD; Department of Radiology, The Second Xiangya Hospital of Central South University, No. 139 Middle Renmin Road, Changsha, 410011, China. xiaoyudong222@csu.edu.cn.
Abdom Radiol (NY) ; 46(2): 581-589, 2021 02.
Article en En | MEDLINE | ID: mdl-32761406
ABSTRACT

OBJECTIVES:

The purpose of the present study is to develop a predictive model for incomplete response (IR) after conventional transarterial chemoembolization (cTACE) for hepatocellular carcinoma (HCC) based on hepatic angiographic and cross-sectional imaging.

METHODS:

Sixty patients with 139 target HCC lesions who underwent cTACE from February 2013 to March 2019 were included in this retrospective study. Hepatic angiographic features were identified the number of feeding arteries, vascularity of the tumor, tumor staining on angiography, vascular lake phenomenon, and hepatic arterio-portal shunt. Cross-sectional imaging features were also identified tumor extent, location, size, and enhancement pattern. Treatment response was assessed by the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria. Logistic regression analysis was performed to determine the potential predictive factors for treatment response. To validate the predictive value of potential factors, the means of a decision tree were also calculated by Classification and Regression Tree (CART). P < 0.05 was considered statistically significant.

RESULTS:

The IR rate was 43.2% (60/139) in the entire study population. Logistic regression analysis showed that a tumor size > 50 mm (P = 0.005; odds ratio, 7.25; 95% CI 1.79-29.33), central location (P = 0.007; odds ratio, 0.14; 95% CI 0.03-0.59), and nondense tumor staining (P < 0.001; odds ratio, 0.08; 95% CI 0.02-0.28) were predictors of IR after cTACE. Decision tree analysis showed a good ability to classify treatment response with an accuracy of 78.4%.

CONCLUSION:

Tumor size > 50 mm, central tumor location, and nondense tumor staining were predictors of IR after cTACE. These factors should be taken into consideration when performing cTACE.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Quimioembolización Terapéutica / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Abdom Radiol (NY) Año: 2021 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Quimioembolización Terapéutica / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Abdom Radiol (NY) Año: 2021 Tipo del documento: Article País de afiliación: China