ArticleCardiovascular and interventional radiology2021
Retrospective Use of Breathing Motion Compensation Technology (MCT) Enhances Vessel Detection Software Performance.
Article in Cardiovascular and interventional radiology, 2021. 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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Who cites it
3 citing papers in PubMed.
- Improving cone-beam computed tomography image quality for transarterial therapy of liver malignancies: Evaluation of a motion correction algorithm with and without automated bone removal.Journal of clinical imaging science · 2025Article
- Precision Imaging Guidance in the Era of Precision Oncology: An Update of Imaging Tools for Interventional Procedures.Journal of clinical medicine · 2022Review
- Application of Digital Image Based on Machine Learning in Media Art Design.Computational intelligence and neuroscience · 2021Article
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Authors and funding
5 authors.
Funding
Abstract
purposeCone beam CT (CBCT) with planning software is used in intra-arterial liver-directed therapies. Software accuracy relies on high CBCT image quality, which can be impaired by breathing motion. We assessed the impact of a specific MCT on software performance for procedure planning and navigation. MATERIALS AND
methodsInstitutional Review Board (IRB)-approved retrospective evaluation of liver-directed therapies from July 2015 to April 2018 was performed. CBCTs with at least one well-defined tumor and noticeable breathing motion were included. Each CBCT was reconstructed with and without breathing MCT (Motion Freeze, GE Healthcare). Automatic tumor-supplying vessel detection was performed on up to 4 tumors in each CBCT reconstruction (Liver ASSIST V.I., GE Healthcare). Vessel detection sensitivity and positive predictive value (PPV) were measured with and without MCT using Digital Subtracted Angiography (DSA) as reference. Preprocedural contrast-enhanced CT was also utilized in some cases to rule out the possibility of extrahepatic supplying vessels.
resultsMCT was applied retrospectively to 18 CBCTs with a total of 30 tumors. At least one supplying vessel was detected for 28/30 (93%) tumors with MCT versus 20/30 (66%) without. On the subgroup of 10 CBCTs (22 tumors, 76 feeders) in which the automatic vessel detection initially worked in both reconstructions, the average sensitivity and PPV increased from 63% (48/76) and 57% (48/84) before MCT to 83% (63/76) and 79% (63/80) after (p = 0.002 and p < 0.001).
conclusionBreathing MCT improves planning software performance in CBCT impaired by breathing motion.
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