The status and challenges for prostate SBRT treatments in United States proton therapy centers: An NRG Oncology practice survey.

A survey was designed to inquire about the practice of proton SBRT treatment for prostate cancer. The survey was distributed to all 30 proton therapy centers in the United States that participate in the National Clinical Trial Network in Feb. 2023. The survey focused on usage, patient selection criteria, prescriptions, target contours, dose constraints, treatment plan optimization and evaluation methods, patient-specific QA, and IGRT methods. Results: We received responses from 25 centers (83% participation). Only 8 respondent proton centers (32%) reported performing SBRT of the prostate. The remaining 17 centers cited three primary reasons for not offering this treatment: no clinical need, lack of volumetric imaging, and/or lack of clinical evidence. Only 1 center cited the reduction in overall reimbursement as a concern for not offering prostate SBRT. Several common practices among the 8 centers offering SBRT for the prostate were noted, such as using Hydrogel spacers, fiducial markers, and MRI for target delineation. Most proton centers (87.5%) utilized pencil beam scanning (PBS) delivery and completed Imaging and Radiation Oncology Core (IROC) phantom credentialing. Treatment planning typically used parallel opposed lateral beams, and consistent parameters for setup and range uncertainties were used for plan optimization and robustness evaluation. Measurements-based patient-specific QA, beam delivery every other day, fiducial contours for IGRT, and total doses of 35-40 GyRBE were consistent across all centers. However, there was no consensus on the risk levels for patient selection. Conclusion: Prostate SBRT is used in about 1/3 of proton centers in the US. There was a significant consistency in practices among proton centers treating with proton SBRT. It is possible that the adoption of proton SBRT may become more common if proton SBRT is more commonly offered in clinical trials.

Proton Pencil-Beam Scanning Stereotactic Body Radiation Therapy and Hypofractionated Radiation Therapy for Thoracic Malignancies: Patterns of Practice Survey and Recommendations for Future Development from NRG Oncology and PTCOG.

Stereotactic body radiation therapy (SBRT) and hypofractionation using pencil-beam scanning (PBS) proton therapy (PBSPT) is an attractive option for thoracic malignancies. Combining the advantages of target coverage conformity and critical organ sparing from both PBSPT and SBRT, this new delivery technique has great potential to improve the therapeutic ratio, particularly for tumors near critical organs. Safe and effective implementation of PBSPT SBRT/hypofractionation to treat thoracic malignancies is more challenging than the conventionally-fractionated PBSPT due to concerns of amplified uncertainties at the larger dose per fraction. NRG Oncology and Particle Therapy Cooperative Group (PTCOG) Thoracic Subcommittee surveyed US proton centers to identify practice patterns of thoracic PBSPT SBRT/hypofractionation. From these patterns, we present recommendations for future technical development of proton SBRT/hypofractionation for thoracic treatment. Amongst other points, the recommendations highlight the need for volumetric image guidance and multiple CT-based robust optimization and robustness tools to minimize further the impact of uncertainties associated with respiratory motion. Advances in direct motion analysis techniques are urgently needed to supplement current motion management techniques.

NRG Oncology and PTCOG Patterns of Practice Survey and Consensus Recommendations on Pencil-Beam Scanning Proton Stereotactic Body Radiation Therapy and Hypofractionated Radiation Therapy for Thoracic Malignancies.

Stereotactic body radiation therapy (SBRT) and hypofractionation using pencil-beam scanning (PBS) proton therapy (PBSPT) is an attractive option for thoracic malignancies. Combining the advantages of target coverage conformity and critical organ sparing from both PBSPT and SBRT, this new delivery technique has great potential to improve the therapeutic ratio, particularly for tumors near critical organs. Safe and effective implementation of PBSPT SBRT/hypofractionation to treat thoracic malignancies is more challenging than the conventionally fractionated PBSPT because of concerns of amplified uncertainties at the larger dose per fraction. The NRG Oncology and Particle Therapy Cooperative Group Thoracic Subcommittee surveyed proton centers in the United States to identify practice patterns of thoracic PBSPT SBRT/hypofractionation. From these patterns, we present recommendations for future technical development of proton SBRT/hypofractionation for thoracic treatment. Among other points, the recommendations highlight the need for volumetric image guidance and multiple computed tomography-based robust optimization and robustness tools to minimize further the effect of uncertainties associated with respiratory motion. Advances in direct motion analysis techniques are urgently needed to supplement current motion management techniques.

Preclinical Ultra-High Dose Rate (FLASH) Proton Radiation Therapy System for Small Animal Studies.

Purpose: Animal studies with ultrahigh dose-rate radiation therapy (FLASH, >40 Gy/s) preferentially spare normal tissues without sacrificing antitumor efficacy compared with conventional dose-rate radiation therapy (CONV). At the University of Washington, we developed a cyclotron-generated preclinical scattered proton beam with FLASH dose rates. We present the technical details of our FLASH radiation system and preliminary biologic results from whole pelvis radiation. Methods and Materials: A Scanditronix MC50 compact cyclotron beamline has been modified to produce a 48.7 MeV proton beam at dose rates between 0.1 and 150 Gy/s. The system produces a 6 cm diameter scattered proton beam (flat to ± 3%) at the target location. Female C57BL/6 mice 5 to 6 weeks old were used for all experiments. To study normal tissue effects in the distal colon, mice were irradiated using the entrance region of the proton beam to the whole pelvis, 18.5 Gy at different dose rates: control, CONV (0.6-1 Gy/s) and FLASH (50-80 Gy/s). Survival was monitored daily and EdU (5-ethynyl-2´-deoxyuridine) staining was performed at 24- and 96-hours postradiation. Cleaved caspase-3 staining was performed 24-hours postradiation. To study tumor control, allograft B16F10 tumors were implanted in the right flank and received 18 Gy CONV or FLASH proton radiation. Tumor growth and survival were monitored. Results: After 18.5 Gy whole pelvis radiation, survival was 100% in the control group, 0% in the CONV group, and 44% in the FLASH group (P < .01). EdU staining showed cell proliferation was significantly higher in the FLASH versus CONV group at both 24-hours and 96-hours postradiation in the distal colon, although both radiation groups showed decreased proliferation compared with controls (P < .05). Lower cleaved caspase-3 staining was seen in the FLASH versus conventional group postradiation (P < .05). Comparable flank tumor control was observed in the CONV and FLASH groups. Conclusions: We present our preclinical FLASH proton radiation system and biologic results showing improved survival after whole pelvis radiation, with equivalent tumor control.

Automated treatment planning for proton pencil beam scanning using deep learning dose prediction and dose-mimicking optimization.

PURPOSE: The purpose of this study is to investigate the use of a deep learning architecture for automated treatment planning for proton pencil beam scanning (PBS). METHODS: A 3-dimensional (3D) U-Net model has been implemented in a commercial treatment planning system (TPS) that uses contoured regions of interest (ROI) binary masks as model inputs with a predicted dose distribution as the model output. Predicted dose distributions were converted to deliverable PBS treatment plans using a voxel-wise robust dose mimicking optimization algorithm. This model was leveraged to generate machine learning (ML) optimized plans for patients receiving proton PBS irradiation of the chest wall. Model training was carried out on a retrospective set of 48 previously-treated chest wall patient treatment plans. Model evaluation was carried out by generating ML-optimized plans on a hold-out set of 12 contoured chest wall patient CT datasets from previously treated patients. Clinical goal criteria and gamma analysis were used to compare dose distributions of the ML-optimized plans against the clinically approved plans across the test patients. RESULTS: Statistical analysis of mean clinical goal criteria indicates that compared to the clinical plans, the ML optimization workflow generated robust plans with similar dose to the heart, lungs, and esophagus while achieving superior dosimetric coverage to the PTV chest wall (clinical mean V95 = 97.6% vs. ML mean V95 = 99.1%, p < 0.001) across the 12 test patients. CONCLUSIONS: ML-based automated treatment plan optimization using the 3D U-Net model can generate treatment plans of similar clinical quality compared to human-driven optimization.

Improved lateral penumbra for proton ocular treatments on a general-purpose spot scanning beamline.

PURPOSE: An ocular applicator that fits a commercial proton snout with an upstream range shifter to allow for treatments with sharp lateral penumbra is described. MATERIALS AND METHODS: The validation of the ocular applicator consisted of a comparison of range, depth doses (Bragg peaks and spread out Bragg peaks), point doses, and 2-D lateral profiles. Measurements were made for three field sizes, 1.5, 2, and 3 cm, resulting in 15 beams. Distal and lateral penumbras were simulated in the treatment planning system for seven range-modulation combinations for beams typical of ocular treatments and a field size of 1.5 cm, and penumbra values were compared to published literature. RESULTS: All the range errors were within 0.5 mm. The maximum averaged local dose differences for Bragg peaks and SOBPs were 2.6% and 1.1%, respectively. All the 30 measured point doses were within +/-3% of the calculated. The measured lateral profiles, analyzed through gamma index analysis and compared to the simulated, had pass rates greater than 96% for all the planes. The lateral penumbra increased linearly with depth, from 1.4 mm at 1 cm depth to 2.5 mm at 4 cm depth. The distal penumbra ranged from 3.6 to 4.4 mm and increased linearly with the range. The treatment time for a single 10 Gy (RBE) fractional dose ranged from 30 to 120 s, depending on the shape and size of the target. CONCLUSIONS: The ocular applicator's modified design allows lateral penumbra similar to dedicated ocular beamlines while enabling planners to use modern treatment tools such as Monte Carlo and full CT-based planning with increased flexibility in beam placement.

Treatment of ocular tumors through a novel applicator on a conventional proton pencil beam scanning beamline.

Treatment of ocular tumors on dedicated scattering-based proton therapy systems is standard afforded due to sharp lateral and distal penumbras. However, most newer proton therapy centers provide pencil beam scanning treatments. In this paper, we present a pencil beam scanning (PBS)-based ocular treatment solution. The design, commissioning, and validation of an applicator mount for a conventional PBS snout to allow for ocular treatments are given. In contrast to scattering techniques, PBS-based ocular therapy allows for inverse planning, providing planners with additional flexibility to shape the radiation field, potentially sparing healthy tissues. PBS enables the use of commercial Monte Carlo algorithms resulting in accurate dose calculations in the presence of heterogeneities and fiducials. The validation consisted of small field dosimetry measurements of point doses, depth doses, and lateral profiles relevant to ocular therapy. A comparison of beam properties achieved through the applicator against published literature is presented. We successfully showed the feasibility of PBS-based ocular treatments.

Vulval dermatoses (venereal and nonvenereal) among female patients presenting to a tertiary care hospital in North India.

Background: The skin and mucosa of the vulva are different from the rest of the human body, as it is derived from all three embryological layers. It is more prone to dermatological diseases, both infectious and noninfectious. Aims and Objectives: Our study was a prospective descriptive study on female patients attending the skin outpatient department with complaints of vulval dermatoses. Our aim was to determine the prevalence of venereal and nonvenereal dermatoses (infectious and non-infectious) along with age-wise distribution of these in our area. Materials and Methods: All female patients presenting with visible skin lesions on the vulva from January 2019 to December 2019 were included in this study. Various diagnostic tests such as Gram staining, Tzanck smear, KOH mount, herpes simplex virus serology, and skin biopsy were performed wherever necessary. Observations and Results: The study included 520 patients in whom 525 lesions were identified. These were grouped under venereal and non-venereal dermatoses. Nonvenereal dermatoses were further grouped under infectious and non-infectious conditions. Maximum patients were in the age group of 21-40 years (50.19%). The most common dermatoses were non-venereal infections, seen in 220 (42.30%) patients followed by non-venereal, non-infectious dermatoses seen in 177 (34.04%) patients whereas venereal dermatoses were seen in 128 (24.61%) patients. Conclusion: Most of the patients were in the reproductive age group, and the prevalence of infectious dermatoses both venereal and non-venereal was much more than that of non-infectious conditions affecting the vulval skin as per our study.

NRG Oncology Survey of Monte Carlo Dose Calculation Use in US Proton Therapy Centers.

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.

Validation and practical implementation of seated position radiotherapy in a commercial TPS for proton therapy.

PURPOSE: This work aims to validate new 6D couch features and their implementation for seated radiotherapy in RayStation (RS) treatment planning system (TPS). MATERIALS AND METHODS: In RS TPS, new 6D couch features are (i) chair support device, (ii) patient treatment option of "Sitting: face towards the front of the chair", and (iii) patient support pitch and roll capabilities. The validation of pitch and roll was performed by comparing TPS generated DRRs with planar x-rays. Dosimetric tests through measurement by 2D ion chamber array were performed for beams created with varied scanning and treatment orientation and 6D couch rotations. For the implementation of 6D couch features for treatments in a seated position, the TPS and oncology information system (Mosaiq) settings are described for a commercial chair. An end-to-end test using an anthropomorphic phantom was performed to test the complete workflow from simulation to treatment delivery. RESULTS: The 6D couch features were found to have a consistent implementation that met IEC 61712 standard. The DRRs were found to have an acceptable agreement with planar x-rays based on visual inspection. For dose map comparison between measured and calculated, the gamma index analysis for all the beams was >95% at a 3% dose-difference and 3 mm distance-to-agreement tolerances. For an end-to end-testing, the phantom was successfully set up at isocenter in the seated position and treatment was delivered. CONCLUSIONS: Chair-based treatments in a seated position can be implemented in RayStation through the use of newly released 6D couch features.

A machine learning-based framework for delivery error prediction in proton pencil beam scanning using irradiation log-files.

PURPOSE: This study aims to investigate the use of machine learning models for delivery error prediction in proton pencil beam scanning (PBS) delivery. METHODS: A dataset of planned and delivered PBS spot parameters was generated from a set of 20 prostate patient treatments. Planned spot parameters (spot position, MU and energy) were extracted from the treatment planning system (TPS) for each beam. Delivered spot parameters were extracted from irradiation log-files for each beam delivery following treatment. The dataset was used as a training dataset for three machine learning models which were trained to predict delivered spot parameters based on planned parameters. K-fold cross validation was employed for hyper-parameter tuning and model selection where the mean absolute error (MAE) was used as the model evaluation metric. The model with lowest MAE was then selected to generate a predicted dose distribution for a test prostate patient within a commercial TPS. RESULTS: Analysis of the spot position delivery error between planned and delivered values resulted in standard deviations of 0.39 mm and 0.44 mm for x and y spot positions respectively. Prediction error standard deviation values of spot positions using the selected model were 0.22 mm and 0.11 mm for x and y spot positions respectively. Finally, a three-way comparison of dose distributions and DVH values for select OARs indicates that the random-forest-predicted dose distribution within the test prostate patient was in closer agreement to the delivered dose distribution than the planned distribution. CONCLUSIONS: PBS delivery error can be accurately predicted using machine learning techniques.

Clinical Monte Carlo versus Pencil Beam Treatment Planning in Nasopharyngeal Patients Receiving IMPT.

PURPOSE: Pencil beam (PB) analytical algorithms have been the standard of care for proton therapy dose calculations. The introduction of Monte Carlo (MC) algorithms may provide more robust and accurate planning and can improve therapeutic benefit. We conducted a dosimetric analysis to quantify the differences between MC and PB algorithms in the clinical setting of dose-painted nasopharyngeal cancer intensity-modulated proton radiotherapy. PATIENTS AND METHODS: Plans of 14 patients treated with PB analytical algorithm optimized and calculated (PBPB) were retrospectively analyzed. The PBPB plans were recalculated using MC to generate PBMC plans and, finally, reoptimized and recalculated with MC to generate MCMC plans. The plans were compared across several dosimetric endpoints and correlated with documented toxicity. Robustness of the planning scenarios (PBPB, PBMC, MCMC) in the presence of setup and range uncertainties was compared. RESULTS: A median decrease of up to 5 Gy (P < .05) was observed in coverage of planning target volume high-risk, intermediate-risk, and low-risk volumes when PB plans were recalculated using the MC algorithm. This loss in coverage was regained by reoptimizing with MC, albeit with a slightly higher dose to normal tissues but within the standard tolerance limits. The robustness of both PB and MC plans remained similar in the presence of setup and range uncertainties. The MC-calculated mean dose to the oral avoidance structure, along with changes in global maximum dose between PB and MC dosimetry, may be associated with acute toxicity-related events. CONCLUSION: Retrospective analyses of plan dosimetry quantified a loss of coverage with PB that could be recovered under MC optimization. MC optimization should be performed for the complex dosimetry in patients with nasopharyngeal carcinoma before plan acceptance and should also be used in correlative studies of proton dosimetry with clinical endpoints.

Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness.

BACKGROUND: Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma. METHODS: Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan. RESULTS: Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures. CONCLUSIONS: MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.

Advanced proton beam dosimetry part II: Monte Carlo vs. pencil beam-based planning for lung cancer.

BACKGROUND: Proton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients. METHODS: With IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing. RESULTS: In this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10-5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10-3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10-3). CONCLUSIONS: MC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Advanced Proton Beam Dosimetry Part I: review and performance evaluation of dose calculation algorithms.

The accuracy of dose calculation is vital to the quality of care for patients undergoing proton beam therapy (PBT). Currently, the dose calculation algorithms available in commercial treatment planning systems (TPS) in PBT are classified into two classes: pencil beam (PB) and Monte-Carlo (MC) algorithms. PB algorithms are still regarded as the standard of practice in PBT, but they are analytical approximations whereas MC algorithms use random sampling of interaction cross-sections that represent the underlying physics to simulate individual particles trajectories. This article provides a brief review of PB and MC dose calculation algorithms employed in commercial treatment planning systems and their performance comparison in phantoms through simulations and measurements. Deficiencies of PB algorithms are first highlighted by a simplified simulation demonstrating the transport of a single sub-spot of proton beam that is incident at an oblique angle in a water phantom. Next, more typical cases of clinical beams in water phantom are presented and compared to measurements. The inability of PB to correctly predict the range and subsequently distal fall-off is emphasized. Through the presented examples, it is shown how dose errors as high as 30% can result with use of a PB algorithm. These dose errors can be minimized to clinically acceptable levels of less than 5%, if MC algorithm is employed in TPS. As a final illustration, comparison between PB and MC algorithm is made for a clinical beam that is use to deliver uniform dose to a target in a lung section of an anthropomorphic phantom. It is shown that MC algorithm is able to correctly predict the dose at all depths and matched with measurements. For PB algorithm, there is an increasing mismatch with the measured doses with increasing tissue heterogeneity. The findings of this article provide a foundation for the second article of this series to compare MC vs. PB based lung cancer treatment planning.

Intensity Modulated Proton Therapy with Advanced Planning Techniques in a Challenging Hepatocellular Carcinoma Patient.

The use of radiation therapy has been increasing over recent years for the treatment of hepatocellular carcinoma (HCC). Proton beam therapy (PBT) has emerged as a promising treatment option for HCC patients due to its dosimetric advantages of sparing more normal liver tissue from radiation at low to moderate doses compared to photon-based treatments while still delivering high doses of radiation to tumors. The PBT therapy may be particularly beneficial in high-risk HCC cirrhotic patients with large, bulky tumors and/or vascular invasion complicated by surrounding perfusion abnormalities. We present a case of a 62-year-old male with an unresectable 13 cm diffusely infiltrative HCC tumor with main portal vein invasion and elevated alpha-feta protein (AFP) of 37,200 that was intolerant of standard sorafenib treatment. He was treated with hypofractionated PBT to 67.5 GyE in 15 fractions using a novel combination of simultaneously integrated boost intensity modulated proton therapy (SIB-IMPT), breath hold technique, and functional liver imaging with technetium-99m [99mTc] sulfur colloid single-photon emission computed tomography (SPECT/CT) to assist in the differentiation of tumor and normal liver. He had a complete radiographic and biochemical response by AFP normalization by seven months post-treatment without evidence of radiation hepatotoxicity.

Biological and dosimetric characterisation of spatially fractionated proton minibeams.

The biological effectiveness of proton beams varies with depth, spot size and lateral distance from the beam central axis. The aim of this work is to incorporate proton relative biological effectiveness (RBE) and equivalent uniform dose (EUD) considerations into comparisons of broad beam and highly modulated proton minibeams. A Monte Carlo model of a small animal proton beamline is presented. Dose and variable RBE is calculated on a per-voxel basis for a range of energies (30-109 MeV). For an open beam, the RBE values at the beam entrance ranged from 1.02-1.04, at the Bragg peak (BP) from 1.3 to 1.6, and at the distal end of the BP from 1.4 to 2.0. For a 50 MeV proton beam, a minibeam collimator designed to produce uniform dose at the depth of the BP peak, had minimal impact on the open beam RBE values at depth. RBE changes were observed near the surface when the collimator was placed flush with the irradiated object, due to a higher neutron contribution derived from proton interactions with the collimator. For proton minibeams, the relative mean RBE weighted entrance dose (RWD) was ~25% lower than the physical mean dose. A strong dependency of the EUD with fraction size was observed. For 20 Gy fractions, the EUD varied widely depending on the radiosensitivity of the cells. For radiosensitive cells, the difference was up to ~50% in mean dose and ~40% in mean RWD and the EUD trended towards the valley dose rather than the mean dose. For comparative studies of uniform dose with spatially fractionated proton minibeams, EUD derived from a per-voxel RWD distribution is recommended for biological assessments of reproductive cell survival and related endpoints.

Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations.

RaySearch Americas Inc. (NY) has introduced a commercial Monte Carlo dose algorithm (RS-MC) for routine clinical use in proton spot scanning. In this report, we provide a validation of this algorithm against phantom measurements and simulations in the GATE software package. We also compared the performance of the RayStation analytical algorithm (RS-PBA) against the RS-MC algorithm. A beam model (G-MC) for a spot scanning gantry at our proton center was implemented in the GATE software package. The model was validated against measurements in a water phantom and was used for benchmarking the RS-MC. Validation of the RS-MC was performed in a water phantom by measuring depth doses and profiles for three spread-out Bragg peak (SOBP) beams with normal incidence, an SOBP with oblique incidence, and an SOBP with a range shifter and large air gap. The RS-MC was also validated against measurements and simulations in heterogeneous phantoms created by placing lung or bone slabs in a water phantom. Lateral dose profiles near the distal end of the beam were measured with a microDiamond detector and compared to the G-MC simulations, RS-MC and RS-PBA. Finally, the RS-MC and RS-PBA were validated against measured dose distributions in an Alderson-Rando (AR) phantom. Measurements were made using Gafchromic film in the AR phantom and compared to doses using the RS-PBA and RS-MC algorithms. For SOBP depth doses in a water phantom, all three algorithms matched the measurements to within ±3% at all points and a range within 1 mm. The RS-PBA algorithm showed up to a 10% difference in dose at the entrance for the beam with a range shifter and >30 cm air gap, while the RS-MC and G-MC were always within 3% of the measurement. For an oblique beam incident at 45°, the RS-PBA algorithm showed up to 6% local dose differences and broadening of distal fall-off by 5 mm. Both the RS-MC and G-MC accurately predicted the depth dose to within ±3% and distal fall-off to within 2 mm. In an anthropomorphic phantom, the gamma index (dose tolerance = 3%, distance-to-agreement = 3 mm) was greater than 90% for six out of seven planes using the RS-MC, and three out seven for the RS-PBA. The RS-MC algorithm demonstrated improved dosimetric accuracy over the RS-PBA in the presence of homogenous, heterogeneous and anthropomorphic phantoms. The computation performance of the RS-MC was similar to the RS-PBA algorithm. For complex disease sites like breast, head and neck, and lung cancer, the RS-MC algorithm will provide significantly more accurate treatment planning.

Functional lung avoidance and response-adaptive escalation (FLARE) RT: Multimodality plan dosimetry of a precision radiation oncology strategy.

PURPOSE: Nonsmall cell lung cancer (NSCLC) patient radiation therapy (RT) is planned without consideration of spatial heterogeneity in lung function or tumor response. We assessed the dosimetric and clinical feasibility of functional lung avoidance and response-adaptive escalation (FLARE) RT to reduce dose to [99m Tc]MAA-SPECT/CT perfused lung while redistributing an escalated boost dose within [18 F]FDG-PET/CT-defined biological target volumes (BTV). METHODS: Eight stage IIB-IIIB NSCLC patients underwent FDG-PET/CT and MAA-SPECT/CT treatment planning scans. Perfused lung objectives were derived from scatter/collimator/attenuation-corrected MAA-SPECT uptake relative to ITV-subtracted lung to maintain < 20 Gy mean lung dose (MLD). Prescriptions included 60 Gy to the planning target volume (PTV) and concomitant boost of 74 Gy mean to biological target volumes (BTV = GTV + PET gradient segmentation) scaled to each BTV voxel by relative FDG-PET SUV. Dose-painting-by-numbers prescriptions were integrated into commercial treatment planning systems via uptake threshold discretization. Dose constraints for lung, heart, cord, and esophagus were defined. FLARE RT plans were optimized with volumetric modulated arc therapy (VMAT), proton pencil beam scanning (PBS) with 3%-3 mm robust optimization, and combination of PBS (avoidance) plus VMAT (escalation). The high boost dose region was evaluated within a standardized SUVpeak structure. FLARE RT plans were compared to reference VMAT plans. Linear regression between radiation dose to BTV and normalized FDG PET SUV at every voxel was conducted, from which Pearson linear correlation coefficients and regression slopes were extracted. Spearman rank correlation coefficients were estimated between radiation dose to lung and normalized SPECT uptake. Dosimetric differences between treatment modalities were evaluated by Friedman nonparametric paired test with multiple sampling correction. RESULTS: No unacceptable violations of PTV and normal tissue objectives were observed in 24 FLARE RT plans. Compared to reference VMAT plans, FLARE VMAT plans achieved a higher mean dose to BTV (73.7 Gy 98195. 61.3 Gy), higher mean dose to SUVpeak (89.7 Gy vs. 60.8 Gy), and lower mean dose to highly perfused lung (7.3 Gy vs. 14.9 Gy). These dosimetric gains came at the expense of higher mean heart dose (9.4 Gy vs. 5.8 Gy) and higher maximum cord dose (50.1 Gy vs. 44.6 Gy) relative to the reference VMAT plans. Between FLARE plans, FLARE VMAT achieved higher dose to the SUVpeak ROI than FLARE PBS (89.7 Gy vs. 79.2 Gy, P = 0.01), while FLARE PBS delivered lower dose to lung than FLARE VMAT (11.9 Gy vs. 15.6 Gy, P < 0.001). Voxelwise linear dose redistribution slope between BTV dose and FDG PET uptake was higher in magnitude for FLARE PBS + VMAT (0.36 Gy per %SUVmax ) compared to FLARE VMAT (0.27 Gy per %SUVmax ) or FLARE PBS alone (0.17 Gy per %SUVmax ). CONCLUSIONS: FLARE RT is clinically feasible with VMAT and PBS. A combination of PBS for functional lung avoidance and VMAT for FDG PET dose escalation balanced target and normal tissue objective tradeoffs. These results provide a technical platform for testing of FLARE RT safety and efficacy within a precision radiation oncology trial.

Clinical Commissioning of a Pencil Beam Scanning Treatment Planning System for Proton Therapy.

PURPOSE: In this report, we present the commissioning and validation results for a commercial proton pencil beam scanning RayStation treatment planning system. MATERIALS AND METHODS: The commissioning data requirements are (1) integrated depth dose curves, (2) spot profiles, (3) absolute dose/monitor unit calibration, and (4) virtual source position. An 8-cm parallel plate chamber was used to measure the integrated depth dose curves by scanning a beam composed of a single spot in a water phantom. The spot profiles were measured at 5 different planes using a 2-dimensional scintillation detector. The absolute dose/monitor unit calibration was based on dose measurements in single-layer fields of size 10 × 10 cm2. The virtual-source position was calculated from the change in spot spacing with the distance from the isocenter. The beam model validation consisted of a comparison against commissioning data as well as a new set of verification measurements. For end-to-end testing, a series of phantom plans were created. These plans were measured at 1 to 3 depths using a 2-dimensional ion chamber array and evaluated for gamma index using the 3% and 3 mm criteria. RESULTS: The maximum deviation for spot sigma measured versus calculated was -0.2 mm. The point-dose measurements for single-layer beams were within ± 3%, except for the largest field size (29 × 29 cm2) and the highest energy (226 MeV). The point doses in the spread-out Bragg peak plans showed a trend in which differences > 3% were seen for ranges > 30 cm, field sizes > 15 × 15 cm2, and depths > 25 cm. For end-to-end testing, 34 planes corresponding to 13 beams were analyzed for gamma index with a minimum pass rate of 92.8%. CONCLUSION: The acceptable verification results and successful end-to-end testing ensured that all components of the treatment planning system were functional and the system was ready for clinical use.