Citations

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.

Background: Post-treatment prognosis and monitoring are critical for determining the timing of salvage treatment in glioblastoma patients but has been challenging due to difficulties differentiating progression from treatment effects in conventional images. This exploratory study aimed to establish the correlation of radiomics image features from time series of amino acid tracer 18F-DOPA PET images, with outcomes, using machine learning and dimension reduction analysis. Methods: 18F-DOPA PET images were collected for a patient cohort with wild-type IDH and unmethylated MGMT who underwent dose-escalated radiation therapy. Quantitative features were derived from the high uptake region (T/N > 2.0) in pre- and post-radiation therapy follow-up 18F-DOPA PET images. A customized workflow was utilized for pre-selecting predictive features, followed by manifold learning. Machine learning algorithms were employed to establish associations between imaging features and remaining survival (RS), defined as the time between a follow-up scan and date of death. Results: The ML models exhibited 81–83% ROC_AUC in predicting RS evaluated on an independent test dataset. A RS map is proposed for monitoring tumor alterations through serial 18F-DOPA PET scans, demonstrating superior sensitivity and better correlation with survival compared to the RANO criteria. Conclusions: Our study demonstrates that ML models utilizing FU 18F-DOPA PET images have the potential to effectively predict future survival outcomes in patients with glioblastoma treated with dose-escalated radiation therapy. The capability to assess changes in tumor over time through imaging can potentially assist in patient stratification and the selection of salvage treatments, while also aiding in distinguishing treatment effects from genuine tumor progression.

Abstract Background Spatially fractionated radiation therapy (SFRT) is a technique that delivers heterogenous dose distributions consisting of alternating regions of high dose “peaks” and low dose “valleys”. Current delivery methods for SFRT using megavoltage x‐rays usually treat large and bulky tumors with brass grid or volumetric modulated arc therapy (VMAT) lattice techniques. The size and spacing of high dose regions in these approaches are typically on the order of centimeters. However, multiple studies have suggested that decreasing these dimensions may improve the therapeutic ratio. Furthermore, a more compact approach to SFRT would allow for a greater number of high dose regions within the tumor, as well as application to smaller and more irregularly shaped targets thereby increasing the number of patients that could benefit from SFRT. Purpose This study describes the commissioning and first patient treatment using mini‐lattice radiation therapy (MLRT). MLRT uses a clinical linear accelerator and decreases the size and spacing of standard lattice SFRT by using individual multileaf collimator (MLC) leaves to deliver 5 mm wide high dose regions. Methods MLRT plans were created in the Varian Eclipse treatment planning system for a Varian Truebeam equipped with Millennium 120 MLCs. MLRT uses 6 MV Flattening Filter Free high dose rate and the width of individual MLCs to define 5 mm by 5 mm openings separated by closed MLCs to deliver alternating opened and blocked regions. Dynamic conformal arcs were used to conform MLCs to 4 mm spherical mini‐lattice structures in the gross tumor volume (GTV). A MLRT‐specific beam model was commissioned to accurately model the small MLRT fields. Film measurements were performed to assess the accuracy of MLRT plans calculations. Plans for seven treatment sites in different parts of the body for retrospective patient candidates were created with varying numbers of mini‐lattices and separation distances to assess the impact of varying these parameters on treatment dose metrics. MLRT was used for the first time to treat a patient with two fractions of MLRT. Results The AcurosXB calculation algorithm with modified x and y spot sizes, dosimetric leaf gap, transmission factor, and output factor table was used to generate a beam model for accurate MLRT calculations. The MLRT‐specific beam model resulted in gamma passing rates (1%/0.5 mm criteria) of 90%–99% for retrospective patient MLRT film measurements. Dose volume histogram statistics, equivalent uniform dose, and mean dose showed a higher number of mini‐lattices with smaller separation increased the dose to the GTV and surrounding tissue. Separation distances between mini‐lattices did not impact plan heterogeneity as measured by D10%/D90%. The first patient treated with the MLRT technique reported pain relief, had stable disease, and no acute toxicities following both fractions. Conclusions MLRT is feasible using clinical linear accelerators and existing radiation oncology infrastructure. It enables targeting smaller tumors with SFRT, allows for a greater number of high dose regions within the target compared to standard VMAT lattice techniques, and may be a useful technique for challenging treatment scenarios.

Abstract Background Conventional proton dose calculation methods are either time‐ and resource‐intensive, like Monte Carlo (MC) simulations, or they sacrifice accuracy, as seen with analytical methods. This trade‐off between computational efficiency and accuracy highlights the need for improved dose calculation approaches in clinical settings. Purpose This study aims to develop a deep‐learning‐based model that calculates dose‐to‐water ( D W ) and dose‐to‐medium ( D M ) using patient anatomy and proton spot map (PSM), achieving approaching MC‐level accuracy with significantly reduced computation time. Additionally, the study seeks to generalize the model to different treatment sites using transfer learning. Methods A SwinUNetr model was developed using 259 four‐field prostate proton stereotactic body radiation therapy (SBRT) plans to calculate patient‐specific D W and D M distributions from CT and projected PSM (PPSM). The PPSM was created by projecting PSM into the CT scans using spot coordinates, stopping power ratio, beam divergence, and water‐equivalent thickness. Fine‐tuning was then performed for the central nervous system (CNS) site using 84 CNS plans. The model's accuracy was evaluated against MC simulation benchmarks using mean absolute error (MAE), gamma analysis (2% local dose difference, 2‐mm distance‐to‐agreement, 10% low dose threshold), and relevant clinical indices on the test dataset. Results The trained model achieved a single‐field dose calculation time of 0.07 s on a Nvidia‐A100 GPU, over 100 times faster than MC simulators. For the prostate site, the best‐performing model showed an average MAE of 0.26 ± 0.17 Gy and a gamma index of 92.2% ± 3.1% in dose regions above 10% of the maximum dose for D W calculations, and an MAE of 0.30 ± 0.19 Gy with a gamma index of 89.7% ± 3.9% for D M calculations. After transfer learning for CNS plans, the model achieved an MAE of 0.49 ± 0.24 Gy and a gamma index of 90.1% ± 2.7% for D W computations, and an MAE of 0.47 ± 0.25 Gy with a gamma index of 85.4% ± 7.1% for D M computations. Conclusions The SwinUNetr model provides an efficient and accurate method for computing dose distributions in proton therapy. It also opens the possibility of reverse‐engineering PSM from D W , potentially speeding up treatment planning while maintaining accuracy.

AbstractPurposeProton treatment plan perturbation by common dental fixtures such as amalgams (Am) and porcelain‐fused‐to‐metal (PFM) crowns has, to date, been uncharacterized. Previous studies have been conducted to determine the physical effect of these materials within the beam path for single spots, but their effects on complex treatment plans and clinical anatomy have not yet been quantified. The present manuscript aims to study the effect of Am and PFM fixtures on proton treatment planning in a clinical setting.MethodsAn anthropomorphic phantom with removable tongue, maxilla, and mandible modules was simulated on a clinical computed tomography (CT) scanner. Spare maxilla modules were modified to include either a 1.5 mm depth central groove occlusal amalgam (Am) or a porcelain‐fused‐to‐metal (PFM) crown, implanted on the first right molar. Modified tongue modules were 3D printed to accommodate several axial or sagittal oriented pieces of EBT‐3 film. Clinically representative spot‐scanning proton plans were generated in Eclipse v.15.6 using the proton convolution superposition (PCS) algorithm v.15.6.06 using a multi‐field optimization (MFO) technique with the goal of delivering a uniform 54 Gy dose to a clinical target volume (CTV) typical of a base‐of‐tongue (BoT) treatment. A typical geometric beam arrangement of two anterior oblique (AO) beams and a posterior beam was employed. Plans optimized without any material overrides were delivered to the phantom A) without implants; B) with Am fixture; or C) with PFM crown. Plans were also reoptimized and delivered with inclusion of material overrides to equate relative stopping power of the fixture with that of a previously measured result.ResultsPlans exhibit slightly greater dose weight towards AO beams. The optimizer accounted for inclusion of fixture overrides by increasing beam weights to the beam closest to the implant. Film measurements exhibited cold spots directly within the beam path through the fixture in plans with and without overridden materials. Cold spots were somewhat mitigated in plans including overridden materials in the structure set but were not entirely eliminated. Cold spots associated with Am and PFM fixtures were quantified at 17% and 14% for plans without overrides, respectively, and 11% and 9% with using Monte Carlo simulation. Compared with film measurements and Monte Carlo simulation, the treatment planning system underestimates the dose shadowing effect in plans including material overrides.ConclusionsDental fixtures create a dose shadowing effect directly in line with the beam path through the material. This cold spot is partially mitigated by overriding the material to measured relative stopping powers. Due to uncertainties in modeling perturbation through the fixture, the magnitude of the cold spot is underestimated using the institutional TPS when compared to measurement and MC simulation.

Abstract BACKGROUND Interpretation of serial magnetic resonance imaging (MRI) for glioblastoma following radiation therapy (RT) is complicated by difficulty differentiating tumor from treatment-related changes, even using updated RANO criteria. The incorporation of novel imaging such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) PET/CT to post-treatment serial imaging may improve prognostication and better facilitate future treatment decisions. METHODS The secondary analysis of a recent phase II prospective clinical trial of 18F-DOPA PET/CT-directed dose-escalated RT included patients with IDH-wildtype, MGMT-unmethylated glioblastoma who underwent post-treatment serial 18F-DOPA PET/CT surveillance. Quantitative features were extracted from pre-RT and post-RT serial PET/CT images, and robust prognostic features were selected using an in-house workflow. Both an automated machine learning (ML) algorithm and an interpretable ML algorithm were utilized to correlate surveillance PET image features with subsequent survival of greater than 12 months versus less than 12 months from the surveillance timepoint. Changes from pre-RT to post-RT PET/CT (delta model) were also assessed for association with post-RT survival and validated with a separate cohort. RESULTS Thirty-five patients with IDH-wildtype, MGMT-unmethylated glioblastoma who had at least one available (range: 1-14) post-treatment 18F-DOPA PET/CT were included. Twenty-four were used for model training, while 11 were used for validation. Ultimately, a five-feature post-RT model utilizing two shape, two texture, and one first-order radiomic feature was selected. For the delta model, five texture, two shape, and one first order radiomic feature were selected. The models show 90% accuracy in predicting survival < 12 months post-surveillance on the training set, and 68%-73% accuracy (AUC 0.64-0.73) for the validation cohort. Delta features were significantly associated with overall survival (p < 0.05). CONCLUSIONS Post-RT serial 18F-DOPA PET/CT imaging can help distinguish true tumor progression in patients with glioblastoma using a radiomics model. Tumor response evaluated for changes from pre-RT to post-RT 18F-DOPA PET/CT also predicted subsequent overall survival.

AbstractPurposeDental fixtures are commonplace in an aging, radiation treatment population. The current, local standard of practice in particle therapy is to employ treatment geometries to avoid delivery through implanted dental fixtures. The present study aims to observe the physical effect of delivering therapeutic proton beams through common dental fixture materials as prelude to an eventual goal of assessing the feasibility of using treatment geometries not specified for avoidance of oral implants. A sampling of common dental materials was selected based on prosthodontic consult and was evaluated in terms of relative stopping power and three‐dimensional (3D) dose perturbation.MethodsAmalgams, porcelain‐fused‐to‐metal (PFM) crowns consisting of zirconia and non‐noble base metals, and lithium disilicate implants were chosen for analysis. Theoretical stopping power (S) and mass stopping power (S/ρ) were calculated using the Stopping and Range of Ions in Matter (SRIM) application, basing stoichiometric compositions of each fixture on published materials data. S and S/ρ were calculated for a range of historically available compositions of amalgams from 1900 until the current era. The perturbance of S and S/ρ as a function of clinically relevant ranges of amalgam compositions for the modern era was analyzed. Water equivalent thickness (WET) and relative stopping power (Srel) of each material was measured for a clinical spot‐scanning proton beam with monoenergies of 159.9 and 228.8 MeV with a multi‐layer ionization chamber (MLIC). Subsequently, 3D dose perturbation was assessed by delivering proton beams through a custom phantom designed to simulate both en‐face and on‐edge treatment geometries through the selected materials. A treatment plan mimicking the experimental delivery was constructed in the institutional treatment planning system and calculated using TOPAS‐based Monte Carlo simulation (MCS). Experimental results were used to validate the MCS. Finally, treatment planning system (TPS) outputs were compared to MCS to determine the accuracy of the dose calculation model.ResultsHistorical compositions of amalgams ranged in S from 44.8 to 42.9 MeV/cm, with the greatest deviation being observed for the 1900–1959 era. Deviation as a function of amalgam composition from the modern era was most sensitive to proportion of Hg, accounting for deviations up to ‐4.2% at the greatest clinically relevant concentration. S/ρ was not found to vary greatly between each porcelain and metal alloy material for PFM type crowns. Relative stopping powers ranged between 1.3 and 5.4 for all studied materials, suggesting substantial changes in proton range with respect to water. Film measurements of pristine spots confirm dose perturbance and shortening of proton range, with an upstream shift of each Bragg peak being observed directly behind the installed fixture. At high energies, cold spots were found in all cases directly behind each material feature with a medial fill‐in of dose occurring distally. Qualitative agreement of spot perturbance was confirmed between film measurements and MCS. Finally, when comparing integrated depth doses (IDD) by summing over all axial directions, good agreement is observed between TPS and MCS.ConclusionsAll dental materials studied substantially perturbed the dosimetry of pristine proton spots both in terms of WET/Srel as well as the spatial distribution of dose. Proton range was quantifiably shortened, and each dental material affected a cold spot directly behind the object with medial dose back‐filling was observed distally. MCS and Eclipse dose calculations exhibited good agreement with measurements, suggesting that treatment planning without employing avoidance strategies may be possible with further investigation.

Abstract While dose escalation of radiotherapy (DERT) has failed to improve overall survival (OS) or progression-free survival (PFS) for glioblastoma in previous studies, a recent phase II clinical trial utilizing 18F-DOPA-PET-directed DERT demonstrated improved PFS in MGMT-unmethylated patients and OS in MGMT-methylated patients compared to historical controls. This planned secondary analysis sought to determine 1) how 18F-DOPA-PET changes RT volumes beyond standard MRI-planning, 2) which patients benefit most and least from this protocol, 3) which are mostly likely to experience clinically significant radionecrosis after DERT, and 4) patterns of failure after DERT. For 69 evaluable patients, median MRI-defined, PET-defined, and combined low-dose gross tumor volumes (GTV51) were 54 cc (range 9-248), 23 cc (0.4-179), and 62 cc (10-260), respectively. Median MRI-defined, PET-defined, and combined high-dose GTVs (GTV76) were 32 cc (range 4-136), 6 cc (0.1-138), and 34 cc (4-162), respectively. 18F-DOPA-PET resulted in a median volumetric expansion of 13% (0-243%) and 5% (0-217%) from MRI-defined low-dose and high-dose GTV’s, respectively. Central failures ( >95% of recurrence tumor volume) occurred within the 76 Gy, 60 Gy, and 51 Gy isodose lines in 32 (46%), 60 (87%), and 64 (93%) patients, respectively. Recursive partitioning analysis stratified patients by OS and PFS. Patients with 18F-DOPA-PET-defined GTV76 > 7.8cc, MRI-defined GTV76 > 42.7cc, and MGMT promotor-unmethylated tumors had the shortest OS, while patients with smaller PET and MRI-defined tumors had the longest OS (median 10.4 vs. 64.6 months, p< 0.001). Similarly, PFS was worst in patients with 18F-DOPA-PET-defined GTV76 > 2.17 cc who had biopsy only (median PFS 3.2 months, p< 0.001). Patients with 18F-DOPA-PET-defined GTV51 > 50 cc had the highest risk of grade 3+ radionecrosis (p< 0.001). In conclusion, larger 18F-DOPA-PET and MRI-defined tumor volumes were associated with worse outcomes, and 18F-DOPA-PET-directed DERT appears to reduce risk of central recurrence in high-dose volumes.