ArticlePhysics in medicine and biology2015
Robustness of target dose coverage to motion uncertainties for scanned carbon ion beam tracking therapy of moving tumors.
Article in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Characterization of animal tissues for Monte Carlo simulations in ion beam therapy.Journal of applied clinical medical physics · 2026Article
- Bevacizumab is an effective treatment for symptomatic cerebral necrosis after carbon ion therapy for recurrent intracranial malignant tumours: A case report.Molecular and clinical oncology · 2022Article
- Management of Motion and Anatomical Variations in Charged Particle Therapy: Past, Present, and Into the Future.Frontiers in oncology · 2022Review
- Robust Angle Selection in Particle Therapy.Frontiers in oncology · 2021Review
- Dosimetric Validation of a System to Treat Moving Tumors Using Scanned Ion Beams That Are Synchronized With Anatomical Motion.Frontiers in oncology · 2021Article
- Proton Therapy For Lymphomas: Current State Of The Art.OncoTargets and therapy · 2019Article
- Article
- Impact of Spot Size and Spacing on the Quality of Robustly Optimized Intensity Modulated Proton Therapy Plans for Lung Cancer.International journal of radiation oncology, biology, physics · 2018Article
- Robust optimization in IMPT using quadratic objective functions to account for the minimum MU constraint.Medical physics · 2018Article
- Particle therapy of moving targets-the strategies for tumour motion monitoring and moving targets irradiation.The British journal of radiology · 2016Review
- Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer.International journal of radiation oncology, biology, physics · 2016Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
Beam tracking with scanned carbon ion radiotherapy achieves highly conformal target dose by steering carbon pencil beams to follow moving tumors using real-time magnetic deflection and range modulation. The purpose of this study was to evaluate the robustness of target dose coverage from beam tracking in light of positional uncertainties of moving targets and beams. To accomplish this, we simulated beam tracking for moving targets in both water phantoms and a sample of lung cancer patients using a research treatment planning system. We modeled various deviations from perfect tracking that could arise due to uncertainty in organ motion and limited precision of a scanned ion beam tracking system. We also investigated the effects of interfractional changes in organ motion on target dose coverage by simulating a complete course of treatment using serial (weekly) 4DCTs from six lung cancer patients. For perfect tracking of moving targets, we found that target dose coverage was high ([Formula: see text] was 94.8% for phantoms and 94.3% for lung cancer patients, respectively) but sensitive to changes in the phase of respiration at the start of treatment and to the respiratory period. Phase delays in tracking the moving targets led to large degradation of target dose coverage (up to 22% drop for a 15° delay). Sensitivity to technical uncertainties in beam tracking delivery was minimal for a lung cancer case. However, interfractional changes in anatomy and organ motion led to large decreases in target dose coverage (target coverage dropped approximately 8% due to anatomy and motion changes after 1 week). Our findings provide a better understand of the importance of each of these uncertainties for beam tracking with scanned carbon ion therapy and can be used to inform the design of future scanned ion beam tracking systems.
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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.