ArticleScientific reports2024
Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- A coarse-to-fine framework combining deep learning and Monte Carlo for BNCT patient position optimization toward inverse planning.Medical physics · 2026Article
- Article
- Boron Neutron Capture Therapy for High-Grade CNS Tumors: Mechanisms, Carriers, and Clinical Progress: A Narrative Review.International journal of molecular sciences · 2026Review
- Development and evaluation of surface-guided patient position system for boron neutron capture therapy.Scientific reports · 2026Article
- The investigation of opening modes of head and neck thermoplastic mask for radiotherapy based on finite element analysis.Radiation oncology (London, England) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of patients for treatment delivery. This study proposes a novel automated robotic-assisted patient positioning system specifically engineered for BNCT applications. The system utilizes high-precision industrial robotics and is fully integrated with NeuMANTA, a proprietary treatment planning system designed for BNCT. Through a systematic workflow, the robotic arm algorithmically calculates and executes the patient's positioning based on the treatment plan, thus enhancing the accuracy and efficacy of the treatment. We validate the positioning system using an anthropomorphic phantom and evaluate the dosimetric impact of positional deviations. The results indicate that the system achieves high accuracy, with a maximum observational deviation of 3 mm in Source-to-Skin Distance (SSD) and 2 mm along the surface. Dosimetric analysis reveals that the resulting dose changes are less than 1% in surface orientation deviations and less than 5% in SSD orientation deviations. The study concludes that the robotic patient positioning system substantially advances in BNCT treatment delivery. This work not only sets a new benchmark for patient positioning in BNCT, but also provides a comprehensive framework for integrating advanced robotics into radiotherapy, paving the way for more precise and effective cancer treatments.
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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 Socratic graph.