ArticleThe international journal of medical robotics + computer assisted surgery : MRCAS2022
Full coverage path planning algorithm for MRgFUS therapy.
Article in The international journal of medical robotics + computer assisted surgery : MRCAS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Preclinical robotic device for magnetic resonance imaging guided focussed ultrasound.The international journal of medical robotics + computer assisted surgery : MRCAS · 2023Article
- Full coverage path planning algorithm for MRgFUS therapy.The international journal of medical robotics + computer assisted surgery : MRCAS · 2022Article
- Workflow of a Preclinical Robotic Magnetic Resonance Imaging-guided Focused Ultrasound Body System.Journal of medical ultrasoundArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundHigh-quality methods for Magnetic Resonance guided Focussed Ultrasound (MRgFUS) therapy planning are needed for safe and efficient clinical practices. Herein, an algorithm for full coverage path planning based on preoperative MR images is presented.
methodsThe software functionalities of an MRgFUS robotic system were enhanced by implementing the developed algorithm. The algorithm's performance in accurate path planning following a Zig-Zag pathway was assessed on MR images. The planned sonication paths were performed on acrylic films using the robotic system carrying a 2.75 MHz single element transducer.
resultsAblation patterns were successfully planned on MR images and produced on acrylic films by overlapping lesions with excellent match between the planned and experimental lesion shapes.
conclusionsThe advanced software was proven efficient in planning and executing full ablation of any segmented target. The reliability of the algorithm could be enhanced through the development of a fully automated segmentation procedure.
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Registered trials
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