ReviewTranslational lung cancer research2018
Advanced Proton Beam Dosimetry Part I: review and performance evaluation of dose calculation algorithms.
Review in Translational lung cancer research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Contour-based lung dose prediction for breast proton therapy.Journal of applied clinical medical physics · 2018Trial
- Commissioning of a Monte Carlo-based scanning proton beam for breast cancer: Incorporating LETd calculations and variable RBE models.Journal of applied clinical medical physics · 2026Article
- Comparison of a Multi-Scenario Robustness Evaluation Method with Measurements for Proton Teletherapy.Cancers · 2025Article
- Current status and upcoming developments for online adaptive proton therapy enabling a closed feedback loop for near real-time adaptation.Frontiers in oncology · 2025Review
- NRG Oncology and Particle Therapy Co-Operative Group Patterns of Practice Survey and Consensus Recommendations on Pencil-Beam Scanning Proton Stereotactic Body Radiation Therapy and Hypofractionated Radiation Therapy for Thoracic Malignancies.International journal of radiation oncology, biology, physics · 2024Review
- Impact of dose calculation accuracy on inverse linear energy transfer optimization for intensity-modulated proton therapy.Precision radiation oncology · 2023Article
- Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?Discover oncology · 2022Article
- Dose calculation accuracy in particle therapy: Comparing carbon ions with protons.Medical physics · 2021Article
- Dose distribution effects of spot-scanning proton beam therapy equipped with a multi-leaf collimator for pediatric brain tumors.Oncology letters · 2021Article
- Physics of Particle Beam and Hypofractionated Beam Delivery in NSCLC.Seminars in radiation oncology · 2021Review
- The influence of beam delivery uncertainty on dose uniformity and penumbra for pencil beam scanning in carbon-ion radiotherapy.PloS one · 2021Article
- Producing a Beam Model of the Varian ProBeam Proton Therapy System using TOPAS Monte Carlo Toolkit.Medical physics · 2020Article
- Treatment planning for proton therapy: what is needed in the next 10 years?The British journal of radiology · 2020Review
- Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness.Radiation oncology (London, England) · 2019Article
- Current status of proton therapy techniques for lung cancer.Radiation oncology journal · 2019Article
- Phantom design and dosimetric characterization for multiple simultaneous cell irradiations with active pencil beam scanning.Radiation and environmental biophysics · 2019Article
- Machine Description File-based Monte Carlo Simulation Modeling and its Validation Using Pencil Beam Scanning Proton Therapy Commissioning Data.Journal of medical physicsArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accuracy of dose calculation is vital to the quality of care for patients undergoing proton beam therapy (PBT). Currently, the dose calculation algorithms available in commercial treatment planning systems (TPS) in PBT are classified into two classes: pencil beam (PB) and Monte-Carlo (MC) algorithms. PB algorithms are still regarded as the standard of practice in PBT, but they are analytical approximations whereas MC algorithms use random sampling of interaction cross-sections that represent the underlying physics to simulate individual particles trajectories. This article provides a brief review of PB and MC dose calculation algorithms employed in commercial treatment planning systems and their performance comparison in phantoms through simulations and measurements. Deficiencies of PB algorithms are first highlighted by a simplified simulation demonstrating the transport of a single sub-spot of proton beam that is incident at an oblique angle in a water phantom. Next, more typical cases of clinical beams in water phantom are presented and compared to measurements. The inability of PB to correctly predict the range and subsequently distal fall-off is emphasized. Through the presented examples, it is shown how dose errors as high as 30% can result with use of a PB algorithm. These dose errors can be minimized to clinically acceptable levels of less than 5%, if MC algorithm is employed in TPS. As a final illustration, comparison between PB and MC algorithm is made for a clinical beam that is use to deliver uniform dose to a target in a lung section of an anthropomorphic phantom. It is shown that MC algorithm is able to correctly predict the dose at all depths and matched with measurements. For PB algorithm, there is an increasing mismatch with the measured doses with increasing tissue heterogeneity. The findings of this article provide a foundation for the second article of this series to compare MC
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