PURPOSE: To evaluate the clinical utility and limitations of a computer software program for detecting tumor feeders of hepatocellular carcinoma (HCC) during transarterial chemoembolization (TACE). MATERIALS AND METHODS:Forty-six patients with 59 HCC nodules underwentnonselective digital subtraction angiography (DSA) and C-arm computed tomography (CT) in the same hepatic artery. C-arm CT data sets were analyzed using the software to identify potential tumor feeders during each TACE session. For DSA analysis, 3 radiologists were independently assigned to identify tumor feeders using the DSA images in a separate session. The sensitivity of the 2 techniques in detecting tumor feeders was compared, with TACE findings as the reference standard. Factors affecting the failure of the software to detect tumor feeders were assessed by univariate and multivariate analyses. RESULTS: We detected 65 tumor feeders supplying 59 HCC nodules during TACE sessions. The sensitivity of the software to detect tumor feeders was significantly higher than that of the manual assessment using DSA (87.7% vs. 71.8%, P<0.001). Multivariate analysis showed that a tumor feeder diameter of <1.0mm (hazard ratio [HR], 56.3; P=0.003) and lipiodol accumulation adjacent to the tumor (HR, 11.4; P=0.044) were the significant predictors for failure to detect tumor feeders. CONCLUSION: The software analysis was superior to manual assessment with DSA in detecting tumor feeders during TACE for HCC. However, the capability of the software to detect tumor feeders was limited by vessel caliber and by prior lipiodol accumulation to the tumor.
RCT Entities:
PURPOSE: To evaluate the clinical utility and limitations of a computer software program for detecting tumor feeders of hepatocellular carcinoma (HCC) during transarterial chemoembolization (TACE). MATERIALS AND METHODS: Forty-six patients with 59 HCC nodules underwent nonselective digital subtraction angiography (DSA) and C-arm computed tomography (CT) in the same hepatic artery. C-arm CT data sets were analyzed using the software to identify potential tumor feeders during each TACE session. For DSA analysis, 3 radiologists were independently assigned to identify tumor feeders using the DSA images in a separate session. The sensitivity of the 2 techniques in detecting tumor feeders was compared, with TACE findings as the reference standard. Factors affecting the failure of the software to detect tumor feeders were assessed by univariate and multivariate analyses. RESULTS: We detected 65 tumor feeders supplying 59 HCC nodules during TACE sessions. The sensitivity of the software to detect tumor feeders was significantly higher than that of the manual assessment using DSA (87.7% vs. 71.8%, P<0.001). Multivariate analysis showed that a tumor feeder diameter of <1.0mm (hazard ratio [HR], 56.3; P=0.003) and lipiodol accumulation adjacent to the tumor (HR, 11.4; P=0.044) were the significant predictors for failure to detect tumor feeders. CONCLUSION: The software analysis was superior to manual assessment with DSA in detecting tumor feeders during TACE for HCC. However, the capability of the software to detect tumor feeders was limited by vessel caliber and by prior lipiodol accumulation to the tumor.
Authors: J C Durack; K T Brown; G Avignon; L A Brody; C T Sofocleous; J P Erinjeri; S B Solomon Journal: Clin Radiol Date: 2018-09-13 Impact factor: 2.350