ArticleMedical physics2016
Robotic intrafractional US guidance for liver SABR: System design, beam avoidance, and clinical imaging.
Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 19 citations in OpenAlex.
- Advancements in artificial intelligence applications for liver ultrasound imaging.BJR artificial intelligence · 2026Review
- Increasing Reachability in Robotic Ultrasound Through Base Placement and Tool Design.The international journal of medical robotics + computer assisted surgery : MRCAS · 2025Article
- Current Research Status of Respiratory Motion for Thorax and Abdominal Treatment: A Systematic Review.Biomimetics (Basel, Switzerland) · 2024Review
- AI-based optimization for US-guided radiation therapy of the prostate.International journal of computer assisted radiology and surgery · 2022Article
- Interpretable Machine Learning for Characterization of Focal Liver Lesions by Contrast-Enhanced Ultrasound.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2022Article
- Case Report: Treatment Planning Study to Demonstrate Feasibility of Transthoracic Ultrasound Guidance to Facilitate Ventricular Tachycardia Ablation With Protons.Frontiers in cardiovascular medicine · 2022Article
- Real-time intrafraction motion monitoring in external beam radiotherapy.Physics in medicine and biology · 2019Review
- Analysis and optimization of the robot setup for robotic-ultrasound-guided radiation therapy.International journal of computer assisted radiology and surgery · 2019Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
Abstract
purposeTo present a system for robotic 4D ultrasound (US) imaging concurrent with radiotherapy beam delivery and estimate the proportion of liver stereotactic ablative body radiotherapy (SABR) cases in which robotic US image guidance can be deployed without interfering with clinically used VMAT beam configurations.
methodsThe image guidance hardware comprises a 4D US machine, an optical tracking system for measuring US probe pose, and a custom-designed robot for acquiring hands-free US volumes. In software, a simulation environment incorporating the LINAC, couch, planning CT, and robotic US guidance hardware was developed. Placement of the robotic US hardware was guided by a target visibility map rendered on the CT surface by using the planning CT to simulate US propagation. The visibility map was validated in a prostate phantom and evaluated in patients by capturing live US from imaging positions suggested by the visibility map. In 20 liver SABR patients treated with VMAT, the simulation environment was used to virtually place the robotic hardware and US probe. Imaging targets were either planning target volumes (PTVs, range 5.9-679.5 ml) or gross tumor volumes (GTVs, range 0.9-343.4 ml). Presence or absence of mechanical interference with LINAC, couch, and patient body as well as interferences with treated beams was recorded.
resultsFor PTV targets, robotic US guidance without mechanical interference was possible in 80% of the cases and guidance without beam interference was possible in 60% of the cases. For the smaller GTV targets, these proportions were 95% and 85%, respectively. GTV size (1/20), elongated shape (1/20), and depth (1/20) were the main factors limiting the availability of noninterfering imaging positions. The robotic US imaging system was deployed in two liver SABR patients during CT simulation with successful acquisition of 4D US sequences in different imaging positions.
conclusionsThis study indicates that for VMAT liver SABR, robotic US imaging of a relevant internal target may be possible in 85% of the cases while using treatment plans currently deployed in the clinic. With beam replanning to account for the presence of robotic US guidance, intrafractional US may be an option for 95% of the liver SABR cases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.