Pencil Beam Algorithms Are Unsuitable for Proton Dose Calculations in Lung
- PMID: 28843371
- PMCID: PMC5729062
- DOI: 10.1016/j.ijrobp.2017.06.003
Pencil Beam Algorithms Are Unsuitable for Proton Dose Calculations in Lung
Abstract
Purpose: To compare analytic and Monte Carlo-based algorithms for proton dose calculations in the lung, benchmarked against anthropomorphic lung phantom measurements.
Methods and materials: A heterogeneous anthropomorphic moving lung phantom has been irradiated at numerous proton therapy centers. At 5 centers the treatment plan could be calculated with both an analytic and Monte Carlo algorithm. The doses calculated in the treatment plans were compared with the doses delivered to the phantoms, which were measured using thermoluminescent dosimeters and film. Point doses were compared, as were planar doses using a gamma analysis.
Results: The analytic algorithms overestimated the dose to the center of the target by an average of 7.2%, whereas the Monte Carlo algorithms were within 1.6% of the physical measurements on average. In some regions of the target volume, the analytic algorithm calculations differed from the measurement by up to 31% in the internal gross target volume (iGTV) (46% in the planning target volume), over-predicting the dose. All comparisons showed a region of at least 15% dose discrepancy within the iGTV between the analytic calculation and the measured dose. The Monte Carlo algorithm recalculations showed dramatically improved agreement with the measured doses, showing mean agreement within 4% for all cases and a maximum difference of 12% within the iGTV.
Conclusions: Analytic algorithms often do a poor job predicting proton dose in lung tumors, over-predicting the dose to the target by up to 46%, and should not be used unless extensive validation counters the consistent results of the present study. Monte Carlo algorithms showed dramatically improved agreement with physical measurements and should be implemented to better reflect actual delivered dose distributions.
Copyright © 2017 Elsevier Inc. All rights reserved.
Conflict of interest statement
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References
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