Efficacy of Automated Supply Artery Tracking Software Using Preoperative Computed Tomography for Renal Carcinoma.

Marina Osaki, Rika Yoshimatsu, Tomohiro Matsumoto, Tomoaki Yamanishi, Hitomi Maeda, Kensuke Osaragi, Junki Shibata, Takashi Karashima, Keiji Inoue, Takuji Yamagami
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Abstract

Purpose: To evaluate the ability of automated supply artery tracking software to detect feeding vessels for renal tumors using preoperative dynamic contrast-enhanced computed tomography. Material and Methods: For 10 sessions in 10 patients in which transarterial embolization was performed before percutaneous ablation therapy for a single renal cell carcinoma, data that had been obtained from dynamic contrast-enhanced computed tomography in the arterial phase were examined. Automated supply artery tracking software was retrospectively applied with arterial phase images of preoperative contrast-enhanced computed tomography, and the extracted feeding vessels were identified by two observers: a radiologist and a radiological technologist. Real supply arteries were determined by arteriography during transarterial embolization. Extracted feeding vessel and real supply arteries were compared. The concordance rate of extracted feeding vessel between observers was examined. Sensitivity and positive predictive value of automated supply artery tracking software and changes in sensitivity and positive predictive value under conversion of the distance recognized as extracted feeding vessel between the tumor and vessels from the preset distance (20 mm) to the cut-off value using receiver operating characteristic curve analysis were investigated. Results: Twenty real supply arteries were identified among 10 cases. Number of extracted feeding vessel was 32 and 34 by the observers. The concordance rate of extracted feeding vessel was 80% (8/10 cases). Sensitivity of automated supply artery tracking software was 70% (14/20) by both observers and positive predictive value was 43.8% (14/32) and 41.2% (14/34) by each observer. When the cut-off value (12.1 mm) replaced distance, positive predictive value was elevated from 43.8% to 73.7% and from 41.2% to 68.4%. Conclusions: Ability of automated supply artery tracking software based on transvenous contrast-enhanced computed tomography was acceptable for identifying feeding vessels of a renal tumor preoperatively.

自动供血动脉追踪软件在肾癌术前计算机断层扫描中的应用效果。
目的:评价自动供血动脉跟踪软件在术前动态增强计算机断层扫描中检测肾肿瘤供血血管的能力。材料和方法:对10例单肾细胞癌患者在经皮消融治疗前进行经动脉栓塞治疗的10个疗程的数据进行了检查,这些数据来自于动脉期动态对比增强计算机断层扫描。自动供血动脉追踪软件回顾性应用于术前对比增强计算机断层扫描的动脉期图像,提取的供血血管由两名观察员识别:一名放射科医生和一名放射技术专家。经动脉栓塞时通过动脉造影确定真实供血动脉。提取供血动脉与真实供血动脉比较。观察者对提取的喂食管的一致性进行了检验。研究自动供血动脉跟踪软件的敏感性和阳性预测值,以及利用受试者工作特征曲线分析将肿瘤与血管之间识别为提取供血血管的距离从预设距离(20mm)转换为截止值后敏感性和阳性预测值的变化。结果:10例患者中鉴定出20条真实供血动脉。经观察,共提取了32条和34条喂食管。提取喂养管的符合率为80%(8/10例)。自动供血动脉追踪软件对两名观测者的敏感性为70%(14/20),阳性预测值分别为43.8%(14/32)和41.2%(14/34)。当截断值(12.1 mm)代替距离时,阳性预测值从43.8%提高到73.7%,从41.2%提高到68.4%。结论:基于经静脉对比增强计算机断层扫描的自动供血动脉追踪软件在术前识别肾肿瘤供血血管方面是可以接受的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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