Detectability of Automated Tumor-feeder Detection Software Using Angio-computed Tomography in Transarterial Chemoembolization for Hepatocellular Carcinoma

利用血管造影计算机断层扫描技术检测自动肿瘤供血细胞检测软件在肝细胞癌经动脉化疗栓塞术中的可检测性

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Abstract

Purpose: To evaluate the performance of automated tumor-feeder detection software in transarterial chemoembolization for hepatocellular carcinoma using angio-computed tomography. Material and Methods: This was a retrospective study of 107 hepatocellular carcinomas in 74 patients who underwent selective transarterial chemoembolization between June 2021 and December 2022. Identification of tumor-feeding arteries on computed tomography during hepatic angiography images acquired prior to chemoembolization with angio-computed tomography was evaluated in two independent methods: analysis by automated tumor-feeder detection software and interpretation by radiologists. The sensitivity and positive predictive value of both were calculated, and the sensitivity was compared with the McNemar test. Differences with p <0.05 were considered statistically significant. Results: Transarterial chemoembolization was applied to 107 hepatocellular carcinoma tumors fed by 114 arteries. No significant difference was observed in sensitivity between the software and the interpretation of radiologists (90.4% vs. 95.6%, p = 0.15). The positive predictive value for the software was 90.4%; that for the interpretation of radiologists was 86.8%. Conclusions: The accuracy of automated tumor-feeder detection software applied to angio-computed tomography was comparable to that of radiologists.

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