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
| Autor: | Meng-Qi Yu, Zishu Zhang, Yu-Dong Xiao, Tian-Cheng Wang, Pei-Yao Tao |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Carcinoma Hepatocellular Urology 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Vascularity Internal medicine Carcinoma medicine Humans Radiology Nuclear Medicine and imaging Chemoembolization Therapeutic Retrospective Studies Radiological and Ultrasound Technology medicine.diagnostic_test business.industry Liver Neoplasms Gastroenterology Angiography Retrospective cohort study Odds ratio Hepatology medicine.disease Treatment Outcome Response Evaluation Criteria in Solid Tumors 030220 oncology & carcinogenesis Hepatocellular carcinoma Radiology medicine.symptom business |
| Zdroj: | Abdominal radiology (New York). 46(2) |
| ISSN: | 2366-0058 |
| Popis: | 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.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). P0.05 was considered statistically significant.The IR rate was 43.2% (60/139) in the entire study population. Logistic regression analysis showed that a tumor size50 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 (P0.001; 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%.Tumor size50 mm, central tumor location, and nondense tumor staining were predictors of IR after cTACE. These factors should be taken into consideration when performing cTACE. |
| Databáze: | OpenAIRE |
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