Search

Proton therapy requires accurate dose calculation for treatment planning to ensure the conformal doses are precisely delivered to the targets. The conversion of CT numbers to material properties is a significant source of uncertainty for dose calculation. The aim of this study is to develop a physics-informed deep learning (PIDL) framework to derive accurate mass density and relative stopping power maps from dual-energy computed tomography (DECT) images. The PIDL framework allows deep learning (DL) models to be trained with a physics loss function, which includes a physics model to constrain DL models. Five DL models were implemented including a fully connected neural network (FCNN), dual-FCNN (DFCNN), and three variants of residual networks (ResNet): ResNet-v1 (RN-v1), ResNet-v2 (RN-v2), and dual-ResNet-v2 (DRN-v2). An artificial neural network (ANN) and the five DL models trained with and without physics loss were explored to evaluate the PIDL framework. Two empirical DECT models were implemented to compare with the PIDL method. DL training data were from CIRS electron density phantom 062M (Computerized Imaging Reference Systems, Inc., Norfolk, VA). The performance of DL models was tested by CIRS adult male, adult female, and 5-year-old child anthropomorphic phantoms. For density map inference, the physics-informed RN-v2 was 3.3%, 2.9% and 1.9% more accurate than ANN for the adult male, adult female, and child phantoms. The physics-informed DRN-v2 was 0.7%, 0.6%, and 0.8% more accurate than DRN-v2 without physics training for the three phantoms, respectfully. The results indicated that physics-informed training could reduce uncertainty when ANN/DL models without physics training were insufficient to capture data structures or derived significant errors. DL models could also achieve better image noise control compared to the empirical DECT parametric mapping methods. The proposed PIDL framework can potentially improve proton range uncertainty by offering accurate material properties conversion from DECT., (© 2022 Institute of Physics and Engineering in Medicine.)

Purpose: While intensity modulated proton therapy can deliver simultaneous integrated boost (SIB) to the dominant intraprostatic lesion (DIL) with high precision, it is sensitive to anatomic changes. We investigated the dosimetric effects from these changes based on pretreatment cone-beam computed tomographic (CBCT) images and identified the most important factors using a multilayer perceptron neural network (MLPNN)., Methods and Materials: DILs were contoured based on coregistered multiparametric magnetic resonance images for 25 previously treated prostate cancer patients. SIB plans were created with (1) prostate clinical target volume - V70 Gy = 98%; (2) DIL - V98 Gy > 95%; and (3) all organs at risk (OARs)"?> within clinical constraints. SIB plans were applied to daily CBCT-based deformed planning computed tomography (CT)"?>. DIL - V98 Gy, bladder/rectum maximum dose (Dmax) and volume changes, femur shifts, and the distance from DIL to organs at riskOARs"?> in both planning computed tomogramsCT"?> and CBCT were calculated. Wilcoxon signed-ranks tests were used to compare the changes. MLPNNs were used to model the change in ΔDIL - V98 Gy > 10% and bladder/rectum Dmax > 80 Gy, and the relative importance factors for the model were provided. The performances of the models were evaluated with receiver operating characteristic curves., Results: Comparing initial plan to the average from evaluation plans, respectively, DIL - V98 Gy was 89.3% ± 19.9% versus 86.2% ± 21.3% ( P  = .151); bladder Dmax 71.9 ± 0.6 Gy versus 74.5 ± 2.9 Gy ( P < .001); and rectum Dmax 70.1 ± 2.4 Gy versus 74.9 ± 9.1Gy ( P  = .007). Bladder and rectal volumes were 99.6% ± 39.5% and 112.8% ± 27.2%, respectively, of their initial volume. The femur shift was 3.16 ± 2.52 mm. In the modeling of ΔDIL V98 Gy > 10%, DIL to rectum distance changes, DIL to bladder distance changes, and rectum volume changes ratio are the 3 most important factors. The areas under the receiver operating characteristic curves were 0.89, 1.00, and 0.99 for the modeling of ΔDIL - V98 Gy > 10%, and bladder and rectum Dmax > 80 Gy, respectively., Conclusions: Dosimetric changes in DIL SIB with intensity modulated proton therapy can be modeled and classified based on anatomic changes on pretreatment images by an MLPNN., (© 2021 The Author(s).)

Purpose/objectives: Monte Carlo (MC) dose calculation has appeared in primary commercial treatment-planning systems and various in-house platforms. Dual-energy computed tomography (DECT) and metal artifact reduction (MAR) techniques complement MC capabilities. However, no publications have yet reported how proton therapy centers implement these new technologies, and a national survey is required to determine the feasibility of including MC and companion techniques in cooperative group clinical trials., Materials/methods: A 9-question survey was designed to query key clinical parameters: scope of MC utilization, validation methods for heterogeneities, clinical site-specific imaging guidance, proton range uncertainties, and how implants are handled. A national survey was distributed to all 29 operational US proton therapy centers on 13 May 2019., Results: We received responses from 25 centers (86% participation). Commercial MC was most commonly used for primary plan optimization (16 centers) or primary dose evaluation (18 centers), while in-house MC was used more frequently for secondary dose evaluation (7 centers). Based on the survey, MC was used infrequently for gastrointestinal, genitourinary, gynecology and extremity compared with other more heterogeneous disease sites ( P < .007). Although many centers had published DECT research, only 3/25 centers had implemented DECT clinically, either in the treatment-planning system or to override implant materials. Most centers (64%) treated patients with metal implants on a case-by-case basis, with a variety of methods reported. Twenty-four centers (96%) used MAR images and overrode the surrounding tissue artifacts; however, there was no consensus on how to determine metal dimension, materials density, or stopping powers., Conclusion: The use of MC for primary dose calculation and optimization was prevalent and, therefore, likely feasible for clinical trials. There was consensus to use MAR and override tissues surrounding metals but no consensus about how to use DECT and MAR for human tissues and implants. Development and standardization of these advanced technologies are strongly encouraged for vendors and clinical physicists., Competing Interests: Conflicts of Interest: Jeffrey D. Bradley, MD, discloses personal fees from Mevion Medical Systems, Inc, AstraZeneca, Varian Medical Systems, and Genentech, outside the submitted work. Zuofeng Li, DSc, is an associate editor of the International Journal of Particle Therapy. Dr Li discloses personal fees from Ion Beam Applications, outside the submitted work. Liyong Lin, PhD, discloses a grant from Varian Medical Systems, outside the submitted work, and a pending patent (to be submitted) for Quantitative Multi Energy Computed Tomography (MECT) for the Characterization of Composition and Density Maps of Artificial and Human Materials in Proton Therapy. Charles B. Simone II, MD, discloses honorarium from Varian Medical Systems, outside the submitted work. Paige A. Taylor, MS, discloses a grant from the National Institutes of Health, during the conduct of the study. The authors have no additional relevant conflicts of interest to disclose., (©Copyright 2021 The Author(s).)

Purpose: Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy., Materials and Methods: The proposed method uses a residual attention cycle-consistent generative adversarial network to bring DECT-to-RSP mapping close to a 1-to-1 mapping by introducing an inverse RSP-to-DECT mapping. To evaluate the proposed method, we retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions and acted as learning targets in the training process for DECT datasets; they were evaluated against results from the proposed method using a leave-one-out cross-validation strategy., Results: The predicted RSP maps showed an average normalized mean square error of 2.83% across the whole body volume and an average mean error less than 3% in all volumes of interest. With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences from ground truth in dose volume histogram metrics for clinical target volumes were less than 0.2 Gy for D 95% and D max with no statistical significance. Maximum difference in dose volume histogram metrics of organs at risk was around 1 Gy on average., Conclusion: These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning-based method and show its potential feasibility for proton treatment planning and dose calculation., Competing Interests: Conflicts of Interest: The authors have no relevant conflicts of interest to disclose., (©Copyright 2020 The Author(s) 2021.)

Purpose: There has been a recent epidemic of human papillomavirus (HPV)-positive oropharyngeal cancer, accounting for 70% to 80% of diagnosed cases. These patients have an overall favorable prognosis and are typically treated with a combination of surgery, chemotherapy, and radiation. Because these patients live longer, they are at risk of secondary malignant neoplasms (SMNs) associated with radiation therapy. Therefore, we assessed the predicted risk of SMNs after adjuvant radiation therapy with intensity-modulated proton therapy (IMPT) compared with intensity modulated photon radiation therapy (IMRT) in patients with HPV- positive oropharyngeal cancers after complete resection., Materials and Methods: Thirteen consecutive patients with HPV-positive oropharyngeal cancers treated with postoperative radiation alone were selected. All patients were treated with pencil beam scanning IMPT to a total dose of 60 Gy in 2 Gy fractions. The IMRT plans were generated for clinical backup and were used for comparative purposes. The SMN risk was calculated based on an organ equivalent dose model for the linear-exponential dose-response curve., Results: Median age of the patient cohort was 63 years (range, 47-73 years). There was no difference in target coverage between IMPT and IMRT plans. We noted significant reductions in mean mandible, contralateral parotid, lung and skin organ equivalent doses with IMPT compared with IMRT plans ( P  < .001). Additionally, a significant decrease in the risk of SMNs with IMPT was observed for all the evaluated organs. Per our analysis, for patients with oropharyngeal cancers diagnosed at a national median age of 54 years with an average life expectancy of 27 years (per national Social Security data), 4 excess SMNs per 100 patients could be avoided by treating them with IMPT versus IMRT., Conclusions: Treatment with IMPT can achieve comparable target dose coverage while significantly reducing the dose to healthy organs, which can lead to fewer predicted SMNs compared with IMRT., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to disclose., (©Copyright 2020 The Author(s).)

Monte Carlo (MC)-based dose calculations are generally superior to analytical dose calculations (ADC) in modeling the dose distribution for proton pencil beam scanning (PBS) treatments. The purpose of this paper is to present a methodology for commissioning and validating an accurate MC code for PBS utilizing a parameterized source model, including an implementation of a range shifter, that can independently check the ADC in commercial treatment planning system (TPS) and fast Monte Carlo dose calculation in opensource platform (MCsquare). The source model parameters (including beam size, angular divergence and energy spread) and protons per MU were extracted and tuned at the nozzle exit by comparing Tool for Particle Simulation (TOPAS) simulations with a series of commissioning measurements using scintillation screen/CCD camera detector and ionization chambers. The range shifter was simulated as an independent object with geometric and material information. The MC calculation platform was validated through comprehensive measurements of single spots, field size factors (FSF) and three-dimensional dose distributions of spread-out Bragg peaks (SOBPs), both without and with the range shifter. Differences in field size factors and absolute output at various depths of SOBPs between measurement and simulation were within 2.2%, with and without a range shifter, indicating an accurate source model. TOPAS was also validated against anthropomorphic lung phantom measurements. Comparison of dose distributions and DVHs for representative liver and lung cases between independent MC and analytical dose calculations from a commercial TPS further highlights the limitations of the ADC in situations of highly heterogeneous geometries. The fast MC platform has been implemented within our clinical practice to provide additional independent dose validation/QA of the commercial ADC for patient plans. Using the independent MC, we can more efficiently commission ADC by reducing the amount of measured data required for low dose "halo" modeling, especially when a range shifter is employed., (© 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: Bronchogenicadenoid cystic carcinoma (ACC) is a rare malignancy particularly challenging to irradiate, largely owing to anatomic location and associated toxicities. Proton beam therapy (PBT) can reduce doses to nearby organs at risk, but only one case report has been published detailing PBT for this neoplasm., Patients and Methods: This study was an institutional review board-approved retrospective chart review of all patients at one institution with bronchogenic ACC treated with PBT. Toxicities were assessed per Common Toxicity Criteria for Adverse Events, version 4.0., Results: Five patients, median age 67 years (range = 40-97 years), were all symptomatic before PBT. Two patients were debulked before PBT, which was delivered at a median 66.6 Gy (RBE) (range, 57.5-80 Gy (RBE)). Two patients received concurrent platinum-based chemotherapy. Symptoms improved in all patients. Acute toxicities included the following: grade 1 fatigue (n = 3), grade 1 dermatitis (n = 2), grade 1 esophagitis (n = 1), grade 2 fatigue (n = 1), grade 2 dermatitis (n = 1), grade 2 esophagitis (n = 2). There was one case of late radiation fibrosis causing bronchial stenosis and requiring a stent, and another of late grade 1 dysphagia. All grade 2 toxicities occurred in patients receiving concurrent chemoradiotherapy. At median follow-up of 10 months (range = 5-47 months), no patient experienced tumor recurrence and none had symptoms impairing daily functioning or quality of life. Although statistically nonsignificant owing to low sample sizes, dosimetric data revealed that PBT numerically reduced doses, most notably to the heart and to low-dose volumes of the lung., Conclusions: This is the largest series to date evaluating PBT for bronchogenic ACC. PBT is associated with low rates of acute and late toxicities and excellent early local control., Competing Interests: Conflicts of Interest: All authors declare that they have no conflicts of interest., (© Copyright 2018 International Journal of Particle Therapy.)

AcurosPT is a Monte Carlo algorithm in the Eclipse 13.7 treatment planning system, which is designed to provide rapid and accurate dose calculations for proton therapy. Computational run-time in minimized by simplifying or eliminating less significant physics processes. In this article, the accuracy of AcurosPT was benchmarked against both measurement and an independent MC calculation, TOPAS. Such a method can be applied to any new MC calculation for the detection of potential inaccuracies. To validate multiple Coulomb scattering (MCS) which affects primary beam broadening, single spot profiles in a Solidwater ® phantom were compared for beams of five selected proton energies between AcurosPT, measurement and TOPAS. The spot Gaussian sigma in AcurosPT was found to increase faster with depth than both measurement and TOPAS, suggesting that the MCS algorithm in AcurosPT overestimates the scattering effect. To validate AcurosPT modeling of the halo component beyond primary beam broadening, field size factors (FSF) were compared for multi-spot profiles measured in a water phantom. The FSF for small field sizes were found to disagree with measurement, with the disagreement increasing with depth. Conversely, TOPAS simulations of the same FSF consistently agreed with measurement to within 1.5%. The disagreement in absolute dose between AcurosPT and measurement was smaller than 2% at the mid-range depth of multi-energy beams. While AcurosPT calculates acceptable dose distributions for typical clinical beams, users are cautioned of potentially larger errors at distal depths due to overestimated MCS and halo implementation., (© 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

Purpose: To determine whether individual liver tumor patients can be safely treated with pencil beam scanning proton therapy. This study reports a planning preparation workflow that can be used for beam angle selection and the evaluation of the efficacy of abdominal compression (AC) to mitigate motion., Methods: Four-dimensional computed tomography scans (4DCT) with and without AC were available from 10 liver tumor patients with fluoroscopy-proven motion reduction by AC, previously treated using photons. For each scan, the motion amplitudes and the motion-induced variation of water-equivalent thickness (ΔWET) in each voxel of the target volume were evaluated during treatment plan preparation. Optimal proton beam angles were selected after volume analysis of the respective beam-specific planning target volume (BSPTV). M ⊥80 and ΔWET 80 derived from the 80th percentiles of perpendicular motion amplitude (M ⊥ ) and ΔWET were compared with and without AC. Proton plans were created on the average CT to achieve target coverage similar to that of the conventional photon treatments. 4D dynamic dose calculation was performed postplan by synchronizing proton beam delivery timing patterns to the 4DCT phases to assess interplay and fractionation effects, and to determine motion criteria for subsequent patient treatment., Results: Selected coplanar beam angles ranged between 180° and 39°, primarily from right lateral (oblique) and posterior (oblique) directions. While AC produced a significant reduction in mean Liver-GTV dose, any reduction in mean heart dose was patient dependent and not significant. Similarly, AC resulted in reductions in M ⊥ , ΔWET, and BSPTV volumes and improved dose degradation (ΔD 95 and ΔD 1 ) within the CTV. For small motion (M ⊥80 < 7 mm and ΔWET 80 < 5 mm), motion mitigation was not needed. For moderate motion (M ⊥80 7-10 mm or ΔWET 80 5-7 mm), AC produced a modest improvement. For large motion (M ⊥80 > 10 mm or ΔWET 80 > 7 mm), AC and/or some other form of mitigation strategies were required., Conclusion: A workflow for screening patients' motion characteristics and optimizing beam angle selection was established for the pencil beam scanning proton therapy treatment of liver tumors. Abdominal compression was found to be useful at mitigation of moderate and large motion., (© 2016 American Association of Physicists in Medicine.)

Purpose: Interest in using collimation for spot scanning proton therapy has recently increased in an attempt to improve the lateral penumbra. To investigate the advantages of such an approach for complex targets, a plan comparison between uncollimated and collimated beam spots was performed for patients with head and neck cancer., Patients and Methods: For 10 patients with head and neck cancer, previously treated with spot scanning proton therapy, uncollimated and collimated treatment plans were created using an in-house treatment-planning system capable of modeling asymmetric-beamlet dose distributions resulting from the use of a dynamic collimation system. Both uncollimated and collimated plans reproduced clinically delivered plans in terms of target coverage. A relative plan comparison was performed using both physical and radiobiological metrics on the organs at risk., Results: The dynamic collimation system improved dose-distribution conformity while preserving target coverage. The median reduction of the mean dose to the esophagus, uninvolved larynx, and uninvolved parotids were -11.9% (minimum to maximum, -6.4% to -24.1%), -7.2% (-0.8% to -60.1%), and -5.2% (-0.2% to -21.5%), respectively, and depended on the organ location relative to the target and radiation beam angle. The collimation did not improve dose to some organs at risk surrounded by the target or located upstream of Bragg peaks because of the priority on the target coverage., Conclusion: In spot scanning proton therapy, the dynamic collimation system generally affords better target conformity, which results in improvement in organ-at-risk sparing in the head and neck region while preserving target coverage. However, the benefits of collimation and the increased complexity should be considered for each patient. Patients with large bilateral targets or organs at risk surrounded by the target showed the least benefit., Competing Interests: Conflicts of interest: This research was supported by IBA (Louvain-la-Neuve, Belgium)., (© Copyright 2016 International Journal of Particle Therapy.)

The space radiation environment imposes increased dangers of exposure to ionizing radiation, particularly during a solar particle event. These events consist primarily of low-energy protons that produce a highly inhomogeneous depth-dose distribution. Here we describe a novel technique that uses pencil beam scanning at extended source-to-surface distances and range shifter (RS) to provide robust but easily modifiable delivery of simulated solar particle event radiation to large animals. Thorough characterization of spot profiles as a function of energy, distance and RS position is critical to accurate treatment planning. At 105 MeV, the spot sigma is 234 mm at 4800 mm from the isocentre when the RS is installed at the nozzle. With the energy increased to 220 MeV, the spot sigma is 66 mm. At a distance of 1200 mm from the isocentre, the Gaussian sigma is 68 mm and 23 mm at 105 MeV and 220 MeV, respectively, when the RS is located on the nozzle. At lower energies, the spot sigma exhibits large differences as a function of distance and RS position. Scan areas of 1400 mm (superior-inferior) by 940 mm (anterior-posterior) and 580 mm by 320 mm are achieved at the extended distances of 4800 mm and 1200 mm, respectively, with dose inhomogeneity <2%. To treat large animals with a more sophisticated dose distribution, spot size can be reduced by placing the RS closer than 70 mm to the surface of the animals, producing spot sigmas below 6 mm., (© The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.)