ArticleCardiovascular and interventional radiology2024
Automated Feeder-Detection Software for Renal Cell Carcinoma Embolization: A Retrospective Evaluation of Detection Rate Using Transarterial Time-Resolved Computed Tomography Angiography.
Article in Cardiovascular and interventional radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Efficacy of Automated Supply Artery Tracking Software Using Preoperative Computed Tomography for Renal Carcinoma.Interventional radiology (Higashimatsuyama-shi (Japan) · 2025Article
- Optimal Virtual-target Definition for Detecting Feeding Arteries of Renal Cell Carcinoma Using Automated Feeder-detection Software.Interventional radiology (Higashimatsuyama-shi (Japan) · 2025Article
- Depiction rate of feeding arteries of renal cell carcinoma on four-dimensional computed tomography angiography.Japanese journal of radiology · 2024Article
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11 authors at 2 institutions in 1 country.
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Abstract
purposeTo evaluate the detection rate of feeding arteries in renal cell carcinoma with automated feeder-detection software and determine the optimal imaging phase for accurate feeder detection with transarterial time-resolved computed tomography angiography. MATERIALS AND
methodsThe performance of automated feeder-detection software was retrospectively evaluated using transarterial renal time-resolved computed tomography angiography images of 15 renal cell carcinomas (mean size, 22.1 mm); the images were obtained via the renal artery using a hybrid angio-CT system with 320-row computed tomography, across nine phases with 0.5-s intervals over a contrast delay time of 1.0-5.0 s. Automated feeder-detection software was applied to each phase in all tumors (135 image series in total). The feeder-detection rate (i.e., sensitivity) in each phase was evaluated, and the number of false feeders demonstrated by the software was counted for each tumor.
resultsA total of 22 feeders were identified. The feeder-detection rate was the highest (95.5% [21/22]) at delay times of 1.5 s and 2.0 s and lower in later phases. At delay times of 1.0 s and 1.5 s, the software demonstrated no or only a few (≤ 3) false feeders in 93.3% (14/15) of the tumors. In later phases, however, many (≥ 4) false feeders were observed in > 50% of tumors.
conclusionThe automated feeder-detection software showed a favorable feeder-detection rate and may be useful in transarterial embolization for renal cell carcinoma. The optimal delay time to avoid the demonstration of false feeders and achieve a high detection accuracy was 1.5 s. LEVEL OF EVIDENCE IV: Case Series.
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