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Dental 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.Amalgams, 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 (SHistorical 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.All dental materials studied substantially perturbed the dosimetry of pristine proton spots both in terms of WET/S

Purpose Our previous work demonstrated that 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA) positron emission tomography (PET) is sensitive and specific for identifying regions of high density and biologically aggressive glioblastoma. The purpose of this prospective phase 2 study was to determine the safety and efficacy of biologic-guided, dose-escalated radiation therapy (DERT) using 18F-DOPA PET in patients with glioblastoma. Methods and Materials Patients with newly diagnosed, histologically confirmed glioblastoma aged ≥18 years without contraindications to 18F-DOPA were eligible. Target volumes included 51, 60, and 76 Gy in 30 fractions with a simultaneous integrated boost, and concurrent and adjuvant temozolomide for 6 months. 18F-DOPA PET imaging was used to guide DERT. The study was designed to detect a true progression-free survival (PFS) at 6 months (PFS6) rate ≥72.5% in O6‐methylguanine methyltransferase (MGMT) unmethylated patients (DE-Un), with an overall significance level (alpha) of 0.20 and a power of 80%. Kaplan-Meier analysis was performed for PFS and overall survival (OS). Historical controls (HCs) included 139 patients (82 unmethylated) treated on prospective clinical trials or with standard RT at our institution. Toxicities were evaluated with Common Terminology Criteria for Adverse Events v4.0. Results Between January 2014 and December 2018, 75 evaluable patients were enrolled (39 DE-Un, 24 methylated [DE-Mth], and 12 indeterminate). PFS6 for DE-Un was 79.5% (95% confidence interval, 63.1%-90.1%). Median PFS was longer for DE-Un patients compared with historical controls (8.7 months vs 6.6 months; P = .017). OS was similarly longer, but the difference was not significant (16.0 vs 13.5 months; P = .13). OS was significantly improved for DE-Mth patients compared with HC-Mth (35.5 vs 23.3 months; P = .049) despite nonsignificant improvement in PFS (10.7 vs 9.0 months; P = .26). Grade 3 central nervous system necrosis occurred in 13% of patients, but treatment with bevacizumab improved symptoms in all cases. Conclusions 18F-DOPA PET–guided DERT appears to be safe, and it significantly improves PFS in MGMT unmethylated glioblastoma. OS is significantly improved in MGMT methylated patients. Further investigation of 18F-DOPA PET biologic guided DERT for glioblastoma is warranted.

Purpose The relative biologic effectiveness (RBE) rises with increasing linear energy transfer toward the end of proton tracks. Presently, there is no consensus on how RBE heterogeneity should be accounted for in breast cancer proton therapy treatment planning. Our purpose was to determine the dosimetric consequences of incorporating a brachial plexus (BP) biologic dose constraint and to describe other clinical implications of biologic planning. Methods and Materials We instituted a biologic dose constraint for the BP in the context of MC1631, a randomized trial of conventional versus hypofractionated postmastectomy intensity modulated proton therapy (IMPT). IMPT plans of 13 patients treated before the implementation of the biologic dose constraint (cohort A) were compared with IMPT plans of 38 patients treated on MC1631 after its implementation (cohort B) using (1) a commercially available Eclipse treatment planning system (RBE = 1.1); (2) an in-house graphic processor unit-based Monte Carlo physical dose simulation (RBE = 1.1); and (3) an in-house Monte Carlo biologic dose (MCBD) simulation that assumes a linear relationship between RBE and dose-averaged linear energy transfer (product of RBE and physical dose = biologic dose). Results Before implementation of a BP biologic dose constraint, the Eclipse mean BP D0.01 cm3 was 107%, and the MCBD estimate was 128% (ie, 64 Gy [RBE = biologic dose] in 25 fractions for a 50-Gy [RBE = 1.1] prescription), compared with 100.0% and 116.0%, respectively, after the implementation of the constraint. Implementation of the BP biologic dose constraint did not significantly affect clinical target volume coverage. MCBD plans predicted greater internal mammary node coverage and higher heart dose than Eclipse plans. Conclusions Institution of a BP biologic dose constraint may reduce brachial plexopathy risk without compromising target coverage. MCBD plan evaluation provides valuable information to physicians that may assist in making clinical judgments regarding relative priority of target coverage versus normal tissue sparing.

Our purpose was to dosimetrically compare volumetric modulated arc therapy (VMAT) lattice radiation therapy (LRT), brass, and proton grid therapy planning techniques and suggest potential clinical applications for each.Four plans delivering 20 Gy in 1 fraction were created for each of 22 patients. Brass and proton grid plans used a single static field and the same beam angle. Proton grid plans used the same beam size and spacing as the brass block. Two VMAT LRT plans were generated for each patient: one with 1-cm diameter lattice points spaced 2-cm center-to-center (2-cm VMAT) and another with 1.5-cm diameter lattice points spaced 3-cm center-to-center (3- cm VMAT). Maximum, minimum, mean, and equivalent uniform dose and the dose to 90%, 50%, 20%, 10%, and 5% (D90%[%], D50%[%], etc) of gross tumor volume (GTV) were reported. D10%/D90% characterized dose heterogeneity. Normal tissue dose was generalized by the maximum dose and volume in cubic centimeters of tissue outside the GTV receiving 30% and 50% of prescription (body-GTV V30%[cmVMAT LRT plans delivered the highest maximum GTV doses while brass and proton plans delivered higher D5%(%), D10%(%), and D20%(%) values. D50%(%), D90%(%), and minimum dose varied little between plan types. Proton and brass plans had the highest dose heterogeneity. Two-centimeter VMAT and brass grid plans had the highest mean GTV doses. Two-centimeter VMAT plans had the highest equivalent uniform dose, followed by 3-cm VMAT, brass, and proton plans. VMAT LRT plans exhibited the lowest normal tissue maximum and body GTV V30%(cmAn in-depth comparison of target and normal tissue dosimetric parameters for common photon and proton grid therapy planning techniques was made. Strengths of each plan type were noted leading to general recommendations on usage.

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.

Our previous work demonstrated that 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (Patients with newly diagnosed, histologically confirmed glioblastoma aged ≥18 years without contraindications toBetween January 2014 and December 2018, 75 evaluable patients were enrolled (39 DE-Un, 24 methylated [DE-Mth], and 12 indeterminate). PFS6 for DE-Un was 79.5% (95% confidence interval, 63.1%-90.1%). Median PFS was longer for DE-Un patients compared with historical controls (8.7 months vs 6.6 months; P = .017). OS was similarly longer, but the difference was not significant (16.0 vs 13.5 months; P = .13). OS was significantly improved for DE-Mth patients compared with HC-Mth (35.5 vs 23.3 months; P = .049) despite nonsignificant improvement in PFS (10.7 vs 9.0 months; P = .26). Grade 3 central nervous system necrosis occurred in 13% of patients, but treatment with bevacizumab improved symptoms in all cases.

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.

To develop a Monte Carlo (MC)-based and robust ion beam therapy optimization system that separates the optimization algorithm from the relative biological effectiveness (RBE) modeling. Robustly optimized dose distributions were calculated and compared across three ion therapy beams (proton, helium, carbon). The effect of different averaging techniques in calculating RBE in mixed beams was also investigated. Ion particles were transported in TOPAS MC. The microdosimetric-kinetic model (MKM) parameter, saturation corrected specific energy ([Formula: see text]), was calculated with a customized MKM implementation in TOPAS MC. Intensity modulated ion therapy robust optimization was performed by a quasi-Newton iterative method based on dose-volume objective function. The robust optimization took setup and range uncertainties into account. In the present work, the biological dose for each individual spot was calculated, and then summed together to calculate total biological dose. In other published works, radiosensitive parameters, such as [Formula: see text], were first averaged over all beam spots within a mixed-beam field, after which biological dose was calculated using the averaged radiosensitive parameters. The difference between the two mixed-beam biological dose calculations was quantified. Robust plans were achieved with the three particle types. The effect of averaging [Formula: see text] depended on particle type. The difference between biological doses calculated with individual [Formula: see text] and averaged [Formula: see text] may be greater than 3% for a carbon beam. MC based radiobiological and robust optimization was made flexible to incorporate dose-volume histogram constraints and to be independent of RBE models. Iterative optimization with RBE models was feasible. Evaluation of the RBE calculation for mixed beam could be necessary if better accuracy was demanded.

Purpose To evaluate the incidence of imaging changes in our pediatric brain tumor population treated with spot-scanning proton therapy and analyze the spatial correlation of imaging changes with a novel biologic dose model. Methods and Materials All pediatric patients treated during the first year of our institution's experience who received a minimum treatment planning dose (TPD) of 5040 cGyE with available follow-up magnetic resonance imaging scans were selected for analysis. Posttreatment magnetic resonance imaging scans were fused with the treatment planning computed tomography. All T1 post–gadolinium enhancement, T2 fluid attenuated inversion recovery changes, TPD, and biologic dose (BD) volumes outside of the original gross tumor volume were contoured for analysis. Results Thirty patients were included in the analysis, 7 of whom developed posttreatment radiologic changes. The volumetric overlap of the T2 fluid attenuated inversion recovery changes and BD volumes was significantly greater than the overlap with the TPD volumes. Median volumetric overlaps of 85%, 18%, and 0% were observed with the BD105%, BD110%, and TPD105%, respectively. A nonsignificant increase in the volumetric overlap of the T1C+ changes and BD volumes was also observed. No correlation was observed between the total volume of BD110%, BD105%, or physical dose 105% and the development of imaging changes. Conclusions Within our pediatric brain tumor population treated with spot-scanning proton therapy, our BD model demonstrated superior volumetric overlap with posttreatment T2 changes compared with the TPD model. Using a BD model in treatment planning for spot-scanning proton therapy may help avoid delivery of excessive BD to critical structures and may help minimize the risk of radiation-related late effects.

BACKGROUND: 18F-DOPA-PET thresholds reliably delineate areas of high-grade astrocytoma not otherwise recognized with standard MRI and may more accurately identify regions of aggressive, high-density disease. Herein we report the preliminary safety and feasibility data from an ongoing phase II study (MC1374; R01CA178200) evaluating 18F-DOPA-PET guided-dose-escalated radiotherapy for glioblastoma. METHODS: Newly diagnosed glioblastoma patients without contra-indications to 18F-DOPA-PET are eligible for study enrollment. Target volumes include: CTV51Gy=T1-gadolinium contrast-enhancing (T1-CE) disease, T2 FLAIR signal abnormality, and low-grade 18F-DOPA-PET uptake, +1cm; CTV60Gy=T1-CE and high-grade 18F-DOPA-PET uptake, +1cm; and CTV76Gy=T1-CE and high-grade 18F-DOPA-PET disease without expansion all given in 30 fractions simultaneously. Patients are followed with 18F-DOPA-PET in addition to standard clinical follow-up. Safety stopping rule specifies that after 10 or more patients have been enrolled, if more than 10% experience any of the following adverse events considered to be at least possibly related to treatment, enrollment will be suspended: Grade 3 or 4 irreversible CNS toxicity, Grade 4 non-hematologic, non-CNS toxicity, any Grade 5 toxicity. Futility analysis (and primary study aim) is powered to consider a success to be an MGMT-unmethylated patient who is without progression within 6 months from the time of craniotomy. If 16 or more successes are observed in the first 25 evaluable patients study will continue. RESULTS: 77 patients have been accrued since December 2013 with 68 evaluable for toxicity. Grade 3 CNS necrosis was noted in 3 (4.4%) patients; 2 additional patients developed symptoms that resolved in the subsequent cycle so did not count towards stopping rule. Other grade 3+ toxicities include: 1 patient with pre-existing vision dysfunction had Grade 4 optic nerve dysfunction; 2 Grade 4 hematologic events and 1 Grade 5 event(sepsis) due to temozolamide-induced cytopenias. CONCLUSION: 18F-DOPA-PET -guided dose escalation appears reasonably safe and tolerable in patients with high-grade glioma.

PURPOSE Accuracy 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. METHODS In 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. RESULTS The 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. CONCLUSION An 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.

Purpose Provide an adaptive multicriteria optimization (MCO) method for intensity-modulated proton therapy (IMPT) utilizing GPU technology. Previously described limitations of MCO such as Pareto approximation and limitation on the number of objectives were addressed. Methods The treatment planning process for IMPT must account for multiple objectives, which requires extensive treatment planning resources. Often a large number of objectives (>10) are required. Hence the need for an MCO algorithm that can handle large number of objectives. The novelty of the MCO method presented here lies on the introduction of the adaptive weighting scheme that can generate a well-distributed and dense representation of the Pareto surface for a large number of objectives in an efficient manner. In our approach the generated Pareto surface is constructed for a set of DVH objectives. The MCO algorithm is based on the augmented weighted Chebychev metric (AWCM) method with an adaptive weighting scheme. This scheme uses the differential evolution (DE) method to generate a set of well-distributed Pareto points. The quality of the Pareto points' distribution in the objective space was assessed quantitatively using the Pareto sampling metric. The MCO algorithm was developed to perform multiple parallel searches to achieve a rapid mapping of the Pareto surface, produce clinically deliverable plans, and was implemented on a GPU cluster. The MCO algorithm was tested on two clinical cases with 10 and 18 objectives. For each case one of the MCO-generated plans was selected for comparison with the clinically generated plan. The MCO plan was randomly selected out of the set of MCO plans that had target coverage similar to the clinically generated plan and the same or better sparing of the organs at risk (OAR). Additionally, a validation study of the AWCM method vs the weighted sum method was performed. Results The adaptive MCO algorithm generated Pareto points on the Pareto hypersurface in a fast (2-3 hr) and efficient manner for 2 cases with 10 and 18 objectives. The MCO algorithm generated a dense and well-distributed set of Pareto points on the objective space, and was able to achieve minimization of the Pareto sampling metric. The selected MCO plan showed an improvement of the DVH objectives in comparison to the clinically optimized plan in both cases. For case one, the MCO plan showed a 48% reduction of the 50% dose to OARs and a 16% reduction of the 1% dose to OARs. For case 2, the MCO plan showed a 72% reduction of the 50% dose to OARs and a 42% reduction of the 1% dose to OARs. The comparison of AWCM to WS showed that the AWCM method has a dosimetric advantage over WS for both patient cases. Conclusion We introduced an adaptive MCO algorithm for IMPT accelerated using GPUs. The algorithm is based on an adaptive method for generating Pareto plans in the objective space. We have shown that the algorithm can provide rapid and efficient mapping of the multicriteria Pareto surface with clinically deliverable plans.

Purpose Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)–based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. Methods and Materials Recently, a fast and accurate graphics processor unit (GPU)–based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LET d ), which makes biological dose (BD) optimization possible. To convert from LET d to BD, a simple linear relation was assumed. By use of this novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. Results Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time ( Conclusions By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small–tumor target patients. This optimizer will be used in an upcoming feasibility trial on LET d painting for radioresistant tumors.

BACKGROUND: Multiple studies have demonstrated that amino acid PET tracers identify aggressive disease beyond what is contrast enhancing on T1-weighted conventional MR (T1CE). In this study, we explored discrepancies between 18F-DOPA PET and conventional MR for defining target volumes in newly diagnosed glioblastoma (GBM) radiotherapy patients. METHODS: In an ongoing NCI-funded trial (NCT:R01CA178200), 18F-DOPA PET was acquired prior to chemoradiation for newly diagnosed GBM patients and incorporated prospectively into the target volumes, modifying low and high dose target volumes, and guiding dose escalation to the most aggressive disease. Based on the results of our pilot biopsy-validation study, two 18F-DOPA PET volumes were defined, one with a T/N threshold >2.0 (PET_high) depicting the most aggressive disease and another with a T/N threshold default of ≥1.5 (PET_low) with modifications if needed by a Nuclear Medicine physician. Both PET volumes were compared with the T1CE+cavity MR volumes for 30 MGMT unmethylated newly diagnosed GBM patients. RESULTS: The PET_low volume extended beyond T2-FLAIR signal abnormality for all patients, and extended beyond standard CTV expansion in 60% of patients. Sixty-seven per cent of patients had at least 20% of the PET_high uptake outside the T1CE volume, and would not have been covered by standard CTV expansion in 8% of patients. The average (range) Dice Similarity Coefficient comparing T1CE with PET_high was 0.3(0.0–0.7). The average (range) Haursdorff maximum distance (cm) between PET uptake and T1CE was found to be 2.4(0.9–7.1). CONCLUSIONS: 18F-DOPA-PET identified regions of biologically active disease outside the T1CE in 67% of patients with significant discordance in volumes. Evaluation of the impact prospective 18F-DOPA PET guidance for dose escalated radiation therapy is under investigation in the ongoing trial.

Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation.An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work.For relatively large and complex three-field head and neck cases, i.e.,100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons.A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

Study the contributors to treatment time as a function of Mini-Ridge Filter (MRF) thickness to determine the optimal choice for breath-hold treatment of lung tumors in a synchrotron-based spot-scanning proton machine.Five different spot-scanning nozzles were simulated in TOPAS: four with MRFs of varying maximal thicknesses (6.15-24.6 mm) and one with no MRF. The MRFs were designed with ridges aligned along orthogonal directions transverse to the beam, with the number of ridges (4-16) increasing with MRF thickness. The material thickness given by these ridges approximately followed a Gaussian distribution. Using these simulations, Monte Carlo data were generated for treatment planning commissioning. For each nozzle, standard and stereotactic (SR) lung phantom treatment plans were created and assessed for delivery time and plan quality.Use of a MRF resulted in a reduction of the number of energy layers needed in treatment plans, decreasing the number of synchrotron spills needed and hence the treatment time. For standard plans, the treatment time per field without a MRF was 67.0 ± 0.1 s, whereas three of the four MRF plans had treatment times of less than 20 s per field; considered sufficiently low for a single breath-hold. For SR plans, the shortest treatment time achieved was 57.7 ± 1.9 s per field, compared to 95.5 ± 0.5 s without a MRF. There were diminishing gains in time reduction as the MRF thickness increased. Dose uniformity of the PTV was comparable across all plans; however, when the plans were normalized to have the same coverage, dose conformality decreased with MRF thickness, as measured by the lung V20%.Single breath-hold treatment times for plans with standard fractionation can be achieved through the use of a MRF, making this a viable option for motion mitigation in lung tumors. For stereotactic plans, while a MRF can reduce treatment times, multiple breath-holds would still be necessary due to the limit imposed by the proton extraction time. To balance treatment time and normal tissue dose, the ideal MRF choice was shown to be the thinnest option that is able to achieve the desired breath-hold timing.

Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm3 and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.