Calculation of water equivalent thickness of materials of arbitrary density, elemental composition and thickness in proton beam irradiation

In proton therapy, the radiological thickness of a material is commonly expressed in terms of water equivalent thickness (WET) or water equivalent ratio (WER). However, the WET calculations required either iterative numerical methods or approximate methods of unknown accuracy. The objective of this study was to develop a simple deterministic formula to calculate WET values with an accuracy of 1 mm for materials commonly used in proton radiation therapy. Several alternative formulas were derived in which the energy loss was calculated based on the Bragg-Kleeman rule (BK), the Bethe-Bloch equation (BB) or an empirical version of the Bethe-Bloch equation (EBB). Alternative approaches were developed for targets that were \u27radiologically thin\u27 or \u27thick\u27. The accuracy of these methods was assessed by comparison to values from an iterative numerical method that utilized evaluated stopping power tables. In addition, we also tested the approximate formula given in the International Atomic Energy Agency\u27s dosimetry code of practice (Technical Report Series No 398, 2000, IAEA, Vienna) and stopping power ratio approximation. The results of these comparisons revealed that most methods were accurate for cases involving thin or low-Z targets. However, only the thick-target formulas provided accurate WET values for targets that were radiologically thick and contained high-Z material. © 2009 Institute of Physics and Engineering in Medicine

A review of radiotherapy-induced late effects research after advanced technology treatments

The number of incident cancers and long-term cancer survivors is expected to increase substantially for at least a decade. Advanced technology radiotherapies, e.g., using beams of protons and photons, offer dosimetric advantages that theoretically yield better outcomes. In general, evidence from controlled clinical trials and epidemiology studies are lacking. To conduct these studies, new research methods and infrastructure will be needed. In the paper, we review several key research methods of relevance to late effects after advanced technology proton-beam and photon-beam radiotherapies. In particular, we focus on the determination of exposures to therapeutic and stray radiation and related uncertainties, with discussion of recent advances in exposure calculation methods, uncertainties, in silico studies, computing infrastructure, electronic medical records, and risk visualization. We identify six key areas of methodology and infrastructure that will be needed to conduct future outcome studies of radiation late effects

The physics of proton therapy

The physics of proton therapy has advanced considerably since it was proposed in 1946. Today analytical equations and numerical simulation methods are available to predict and characterize many aspects of proton therapy. This article reviews the basic aspects of the physics of proton therapy, including proton interaction mechanisms, proton transport calculations, the determination of dose from therapeutic and stray radiations, and shielding design. The article discusses underlying processes as well as selected practical experimental and theoretical methods. We conclude by briefly speculating on possible future areas of research of relevance to the physics of proton therapy

A simple and fast physics-based analytical method to calculate therapeutic and stray doses from external beam, megavoltage x-ray therapy

State-of-the-art radiotherapy treatment planning systems provide reliable estimates of the therapeutic radiation but are known to underestimate or neglect the stray radiation exposures. Most commonly, stray radiation exposures are reconstructed using empirical formulas or lookup tables. The purpose of this study was to develop the basic physics of a model capable of calculating the total absorbed dose both inside and outside of the therapeutic radiation beam for external beam photon therapy. The model was developed using measurements of total absorbed dose in a water-box phantom from a 6 MV medical linear accelerator to calculate dose profiles in both the in-plane and cross-plane direction for a variety of square field sizes and depths in water. The water-box phantom facilitated development of the basic physical aspects of the model. RMS discrepancies between measured and calculated total absorbed dose values in water were less than 9.3% for all fields studied. Computation times for 10 million dose points within a homogeneous phantom were approximately 4 min. These results suggest that the basic physics of the model are sufficiently simple, fast, and accurate to serve as a foundation for a variety of clinical and research applications, some of which may require that the model be extended or simplified based on the needs of the user. A potentially important advantage of a physics-based approach is that the model is more readily adaptable to a wide variety of treatment units and treatment techniques than with empirical models

Development and verification of an analytical algorithm to predict absorbed dose distributions in ocular proton therapy using Monte Carlo simulations

Proton beam radiotherapy is an effective and non-invasive treatment for uveal melanoma. Recent research efforts have focused on improving the dosimetric accuracy of treatment planning and overcoming the present limitation of relative analytical dose calculations. Monte Carlo algorithms have been shown to accurately predict dose per monitor unit (D/MU) values, but this has yet to be shown for analytical algorithms dedicated to ocular proton therapy, which are typically less computationally expensive than Monte Carlo algorithms. The objective of this study was to determine if an analytical method could predict absolute dose distributions and D/MU values for a variety of treatment fields like those used in ocular proton therapy. To accomplish this objective, we used a previously validated Monte Carlo model of an ocular nozzle to develop an analytical algorithm to predict three-dimensional distributions of D/MU values from pristine Bragg peaks and therapeutically useful spread-out Bragg peaks (SOBPs). Results demonstrated generally good agreement between the analytical and Monte Carlo absolute dose calculations. While agreement in the proximal region decreased for beams with less penetrating Bragg peaks compared with the open-beam condition, the difference was shown to be largely attributable to edge-scattered protons. A method for including this effect in any future analytical algorithm was proposed. Comparisons of D/MU values showed typical agreement to within 0.5%. We conclude that analytical algorithms can be employed to accurately predict absolute proton dose distributions delivered by an ocular nozzle. © 2010 Institute of Physics and Engineering in Medicine

Visualization of risk of radiogenic second cancer in the organs and tissues of the human body

Background: Radiogenic second cancer is a common late effect in long term cancer survivors. Currently there are few methods or tools available to visually evaluate the spatial distribution of risks of radiogenic late effects in the human body. We developed a risk visualization method and demonstrated it for radiogenic second cancers in tissues and organs of one patient treated with photon volumetric modulated arc therapy and one patient treated with proton craniospinal irradiation. Methods: Treatment plans were generated using radiotherapy treatment planning systems (TPS) and dose information was obtained from TPS. Linear non-threshold risk coefficients for organs at risk of second cancer incidence were taken from the Biological Effects of Ionization Radiation VII report. Alternative risk models including linear exponential model and linear plateau model were also examined. The predicted absolute lifetime risk distributions were visualized together with images of the patient anatomy. Results: The risk distributions of second cancer for the two patients were visually presented. The risk distributions varied with tissue, dose, dose-risk model used, and the risk distribution could be similar to or very different from the dose distribution. Conclusions: Our method provides a convenient way to directly visualize and evaluate the risks of radiogenic second cancer in organs and tissues of the human body. In the future, visual assessment of risk distribution could be an influential determinant for treatment plan scoring

Risk of Secondary Malignant Neoplasms From Proton Therapy and Intensity-Modulated X-Ray Therapy for Early-Stage Prostate Cancer

Purpose: To assess the risk of a secondary malignant neoplasm (SMN) from proton therapy relative to intensity-modulated radiation therapy (IMRT) using X-rays, taking into account contributions from both primary and secondary sources of radiation, for prostate cancer. Methods and Materials: A proton therapy plan and a 6-MV IMRT plan were constructed for 3 patients with early-stage adenocarcinoma of the prostate. Doses from the primary fields delivered to organs at risk of developing an SMN were determined from treatment plans. Secondary doses from the proton therapy and IMRT were determined from Monte Carlo simulations and available measured data, respectively. The risk of an SMN was estimated from primary and secondary doses on an organ-by-organ basis by use of risk models from the Committee on the Biological Effects of Ionizing Radiation. Results: Proton therapy reduced the risk of an SMN by 26% to 39% compared with IMRT. The risk of an SMN for both modalities was greatest in the in-field organs. However, the risks from the in-field organs were considerably lower with the proton therapy plan than with the IMRT plan. This reduction was attributed to the substantial sparing of the rectum and bladder from exposure to the therapeutic beam by the proton therapy plan. Conclusions: When considering exposure to primary and secondary radiation, proton therapy can reduce the risk of an SMN in prostate patients compared with contemporary IMRT. © 2009 Elsevier Inc. All rights reserved