Ma, Jiasen

Abstract Objective. Proton minibeam radiation therapy (pMBRT) is a novel spatially fractionated radiation therapy technique that offers improved tumor control and reduced normal tissue toxicity. However, its clinical translation has been hindered in part by limited field sizes, low dose rates, and complex manufacturing. This work describes the design, manufacturing, and commissioning of a novel divergent pMBRT collimator along with accessory components to maximize its versatility and facilitate clinical implementation. Approach. The dosimetric outcomes for pMBRT collimator geometry, including slit width, center-to-center (CTC) spacing, thickness, divergence, and field size, were evaluated using TOPAS Monte Carlo (MC) to maximize surface peak-to-valley dose ratio (PVDR) while maintaining uniform target coverage. The collimator was constructed using brass plates held by aluminum side holders. Commissioning measurements with a PTW Bragg peak chamber and EBT4 radiochromic film were compared to TOPAS and an in-house fast GPU-based MC simulation. Ancillary equipment consisting of lead foils, range shifters, custom apertures, and secondary pMBRT collimators were characterized in tandem. Main results. An optimized divergent pMBRT collimator with 0.5 mm slit width, 2.0 mm CTC distance, and 40 mm thickness produced a surface PVDR of 4.8 while preserving quasi-homogeneous dose in the 6–14 cm depth region. Measured dose profiles demonstrated valley dose agreement within 3% for both TOPAS and GPU-based MC predictions after the simulated collimator geometry was refined to match Bragg-peak chamber average dose measurements. The onset of the quasi-homogeneous dose region was shifted toward shallower depths by using thin lead foils, without significantly impacting entrance PVDR. Apertures sharpened penumbra and enhanced peripheral PVDR. A dual collimator approach produced 2D pinhole dose arrays that resulted in valley doses from MC simulations and film measurements agreeing within ∼5%. Significance. We demonstrated a practical low-cost, large-area divergent physical pMBRT collimation system with validated MC modeling. In addition, we introduce complementary accessories that substantially expand system versatility to facilitate clinical implementation.

Purpose: This study aimed to compare long-term patient-reported outcomes in bowel and urinary domains between intensity-modulated radiotherapy (IMRT) and intensity-modulated proton therapy (IMPT) for localized prostate cancer. Methods and Materials: Patients with clinical T1–T2 prostate cancer receiving IMRT or IMPT at a tertiary cancer center from 2015–2018 were analyzed to determine the changes in the prospectively collected bowel function (BF), urinary irritative/obstructive symptoms (UO), and urinary incontinence (UI) domains of EPIC-26. The mean changes in EPIC-26 scores were evaluated from pretreatment to 24 months post-radiotherapy for each modality. A score change >50% of the baseline standard deviation was considered a clinically meaningful change. Results: A total of 82 patients treated with IMRT (52.2%) and 56 patients treated with IMPT (53.3%) completed the questionnaire at baseline and 24 months post-RT. There were no baseline differences in domain scores between treatment modalities. At 24 months post-radiotherapy, there was a significant and clinically meaningful decline in the BF mean score in the IMRT cohort (−4.52 (range −50, 29.17), p = 0.003), whereas the decline in BF score did not reach clinical relevance or significance (−1.88 (range −37.5, 50), p = 0.046) when accounting for the Bonferroni adjustment in the IMPT cohort. A higher proportion of patients treated with IMRT had a clinically relevant reduction in BF when compared with IMPT (47.37% vs. 25.93%, p = 0.017). The mean changes in the UI and UO scores of the IMRT and IMPT cohorts were neither statically significant nor clinically relevant. Conclusions: IMPT leads to a smaller decrease in BF than IMRT at 24 months post-RT, while there was no differential effect on UO and UI.

PurposeAccuracy of dose calculation models and robustness under various uncertainties are key factors influencing the quality of intensity modulated proton therapy (IMPT) plans. To mitigate the effects of uncertainties and to improve the dose calculation accuracy, an all‐scenario robust IMPT optimization based on accurate Monte Carlo (MC) dose calculation was developed.MethodsIn the all‐scenario robust IMPT optimization, dose volume histograms (DVHs) were computed for the nominal case and for each uncertainty scenario. All scenarios were weighted by DVH values dynamically throughout optimization iterations. In contrast, probabilistic approach weighted scenarios with fixed scenario weights and worst case optimizations picked one single scenario — the worst scenario for each iteration. Uncertainties in patient setup and proton range were considered in all clinical cases studied. Graphics processing unit (GPU) computation was employed to reduce the computational time in both the MC dose calculation and optimization stages. A previously published adaptive quasi‐Newton method for proton optimization was extended to include robustness. To validate the all‐scenario algorithm extension, it was compared with the single scenario optimization target volume (OTV) based approach in clinical cases of three different disease sites. Additional comparisons with worst case optimization methods were conducted to evaluate the performance of the all‐scenario robust optimization against other robust optimizations.ResultsThe all‐scenario robust IMPT optimization spared organs at risk (OARs) better than the OTV‐based method while maintaining target coverage and improving the robustness of targets and OARs. Compared with composite and voxel‐wise worst case optimization, the all‐scenario robust optimization converged faster, and arrived at solutions of tighter DVH robustness spread, better target coverage and lower OAR dose.ConclusionAn all‐scenario robust IMPT treatment planning system was developed using an adaptive quasi‐Newton optimization method. The optimization system was GPU‐accelerated and based on MC dose calculation. Improved performance was observed in clinical cases when compared with worst case optimization methods.