A Liu

Clinical Implementation of Intensity Modulated Proton Therapy for Thoracic Malignancies

PURPOSE Intensity modulated proton therapy (IMPT) can improve dose conformality and better spare normal tissue over passive scattering techniques, but range uncertainties complicate its use, particularly for moving targets. We report our early experience with IMPT for thoracic malignancies in terms of motion analysis and management, plan optimization and robustness, and quality assurance. METHODS AND MATERIALS Thirty-four consecutive patients with lung/mediastinal cancers received IMPT to a median 66 Gy(relative biological equivalence [RBE]). All patients were able to undergo definitive radiation therapy. IMPT was used when the treating physician judged that IMPT conferred a dosimetric advantage; all patients had minimal tumor motion (<5 mm) and underwent individualized tumor-motion dose-uncertainty analysis and 4-dimensional (4D) computed tomographic (CT)-based treatment simulation and motion analysis. Plan robustness was optimized by using a worst-case scenario method. All patients had 4D CT repeated simulation during treatment. RESULTS IMPT produced lower mean lung dose (MLD), lung V5 and V20, heart V40, and esophageal V60 than did IMRT (P<.05) and lower MLD, lung V20, and esophageal V60 than did passive scattering proton therapy (PSPT) (P<.05). D5 to the gross tumor volume and clinical target volume was higher with IMPT than with intensity modulated radiation therapy or PSPT (P<.05). All cases were analyzed for beam-angle-specific motion, water-equivalent thickness, and robustness. Beam angles were chosen to minimize the effect of respiratory motion and avoid previously treated regions, and the maximum deviation from the nominal dose-volume histogram values was kept at <5% for the target dose and met the normal tissue constraints under a worst-case scenario. Patient-specific quality assurance measurements showed that a median 99% (range, 95% to 100%) of the pixels met the 3% dose/3 mm distance criteria for the γ index. Adaptive replanning was used for 9 patients (26.5%). CONCLUSIONS IMPT using 4D CT-based planning, motion management, and optimization was implemented successfully and met our quality assurance parameters for treating challenging thoracic cancers.

Validation of a track repeating algorithm for intensity modulated proton therapy: Clinical cases study

Monte Carlo (MC) methods are acknowledged as the most accurate technique to calculate dose distributions. However, due its lengthy calculation times, they are difficult to utilize in the clinic or for large retrospective studies. Track-repeating algorithms, based on MC-generated particle track data in water, accelerate dose calculations substantially, while essentially preserving the accuracy of MC. In this study, we present the validation of an efficient dose calculation algorithm for intensity modulated proton therapy, the fast dose calculator (FDC), based on a track-repeating technique. We validated the FDC algorithm for 23 patients, which included 7 brain, 6 head-and-neck, 5 lung, 1 spine, 1 pelvis and 3 prostate cases. For validation, we compared FDC-generated dose distributions with those from a full-fledged Monte Carlo based on GEANT4 (G4). We compared dose-volume-histograms, 3D-gamma-indices and analyzed a series of dosimetric indices. More than 99% of the voxels in the voxelized phantoms describing the patients have a gamma-index smaller than unity for the 2%/2 mm criteria. In addition the difference relative to the prescribed dose between the dosimetric indices calculated with FDC and G4 is less than 1%. FDC reduces the calculation times from 5 ms per proton to around 5 μs.

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

PURPOSE To determine the patient throughput and the overall efficiency of the spot scanning system by analyzing treatment time, equipment availability, and maximum daily capacity for the current spot scanning port at Proton Therapy Center Houston and to assess the daily throughput capacity for a hypothetical spot scanning proton therapy center. METHODS At their proton therapy center, the authors have been recording in an electronic medical record system all treatment data, including disease site, number of fields, number of fractions, delivered dose, energy, range, number of spots, and number of layers for every treatment field. The authors analyzed delivery system downtimes that had been recorded for every equipment failure and associated incidents. These data were used to evaluate the patient census, patient distribution as a function of the number of fields and total target volume, and equipment clinical availability. The duration of each treatment session from patient walk-in to patient walk-out of the spot scanning treatment room was measured for 64 patients with head and neck, central nervous system, thoracic, and genitourinary cancers. The authors retrieved data for total target volume and the numbers of layers and spots for all fields from treatment plans for a total of 271 patients (including the above 64 patients). A sensitivity analysis of daily throughput capacity was performed by varying seven parameters in a throughput capacity model. RESULTS The mean monthly equipment clinical availability for the spot scanning port in April 2012-March 2015 was 98.5%. Approximately 1500 patients had received spot scanning proton therapy as of March 2015. The major disease sites treated in September 2012-August 2014 were the genitourinary system (34%), head and neck (30%), central nervous system (21%), and thorax (14%), with other sites accounting for the remaining 1%. Spot scanning beam delivery time increased with total target volume and accounted for approximately 30%-40% of total treatment time for the total target volumes exceeding 200 cm(3), which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. CONCLUSIONS The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.

Differences in lung injury after IMRT or proton therapy assessed by 18FDG PET imaging

BACKGROUND AND PURPOSE To compare lung injury among non-small cell lung cancer (NSCLC) patients treated with IMRT or proton therapy as revealed by 18F-FDG post-treatment uptake and to determine factors predictive for clinically symptomatic radiation pneumonitis. MATERIAL AND METHODS For 83 patients treated with IMRT or proton therapy, planning CT and follow up 18F-FDG PET-CT were analyzed. Post-treatment PET-CT was aligned with planning CT to establish a voxel-to-voxel correspondence between PET and planning dose images. 18F-FDG uptake as a function of radiation dose to normal lung was obtained for each patient. PET image-derived parameters as well as demographic, clinical, treatment and dosimetric patient characteristics were correlated with clinical symptoms of pneumonitis. RESULTS The dose distributions for the two modalities were significantly different; V5 was higher for IMRT, whereas V60 was higher for protons. The mean lung dose (MLD) was similar for the two modalities. The slope of linear 18F-FDG-uptake - dose response did not differ significantly between the two modalities. The MLD, slope, and 95th percentile of SUV were identified as three major factors associated with radiation pneumonitis. CONCLUSIONS Despite significantly different dose distributions for IMRT and for protons, the slope of the SUV-dose linear regression line previously shown to be associated with RP did not differ between IMRT and protons. Patients who developed radiation pneumonitis had statistically significantly higher MLD and higher slope regardless of treatment modality.

Intensity-Modulated Proton Therapy Adaptive Planning for Patients with Oropharyngeal Cancer

Purpose The authors aimed to illustrate the potential dose differences to clinical target volumes (CTVs) and organs-at-risk (OARs) volumes after proton adaptive treatment planning was used. Patients and Methods The records of 10 patients with oropharyngeal cancer were retrospectively reviewed. Each patients treatment plan was generated by using the Eclipse treatment planning system. Verification computed tomography (CT) scan was performed during the fourth week of treatment. Deformable image registrations were performed between the 2 CT image sets, and the CTVs and major OARs were transferred to the verification CT images to generate the adaptive plan. We compared the accumulated doses to CTVs and OARs between the original and adaptive plans, as well as between the adaptive and verification plans to simulate doses that would have been delivered if the adaptive plans were not used. Results Body contours were different on planning and week-4 verification CTs. Mean volumes of all CTVs were reduced by 4% to 8% (P ≤ .04), and the volumes of left and right parotid glands also decreased (by 11% to 12%, P ≤ .004). Brainstem and oral cavity volumes did not significantly differ (all P ≥ .14). All mean doses to the CTV were decreased for up to 7% (P ≤ .04), whereas mean doses to the right parotid and oral cavity increased from a range of 5% to 8% (P ≤ .03), respectively. Conclusion Verification and adaptive planning should be recommended during the course of proton therapy for patients with head and neck cancer to ensure adequate dose deliveries to the planned CTVs, while safe doses to OARs can be respected.

SU‐F‐T‐122: 4Dand 5D Proton Dose Evaluation with Monte Carlo

PURPOSE We evaluated uncertainties in therapeutic proton doses of a lung treatment, taking into account intra-fractional geometry changes, such as breathing, and inter-fractional changes, such as tumor shrinkage and weight loss. METHODS A Monte Carlo study was performed using four dimensional CT image sets (4DCTs) and weekly repeat imaging (5DCTs) to compute fixed RBE (1.1) and variable RBE weighted dose in an actual lung treatment geometry. The MC2 Monte Carlo system was employed to simulate proton energy deposition and LET distributions according to a thoracic cancer treatment plan developed with a 3D-CT in a commercial treatment planning system, as well as in each of the phases of 4DCT sets which were recorded weekly throughout the course of the treatment. A cumulative dose distribution in relevant structures was computed and compared to the predictions of the treatment planning system. RESULTS Using the Monte Carlo method, dose deposition estimates with the lowest possible uncertainties were produced. Comparison with treatment planning predictions indicates that significant uncertainties may be associated with therapeutic lung dose prediction from treatment planning systems, depending on the magnitude of inter- and intra-fractional geometry changes. CONCLUSION As this is just a case study, a more systematic investigation accounting for a cohort of patients is warranted; however, this is less practical because Monte Carlo simulations of such cases require enormous computational resources. Hence our study and any future case studies may serve as validation/benchmarking data for faster dose prediction engines, such as the track repeating algorithm, FDC.

SU-F-T-195: Systematic Constraining of Contralateral Parotid Gland Led to Improved Dosimetric Outcomes for Multi-Field Optimization with Scanning Beam Proton Therapy: Promising Results From a Pilot Study in Patients with Base of Tongue Carcinoma

PURPOSE Treatment planning for Intensity Modulated Proton Therapy (IMPT) for head and neck cancer is time-consuming due to the large number of organs-at-risk (OAR) to be considered. As there are many competing objectives and also wide range of acceptable OAR constraints, the final approved plan may not be most optimal for the given structures. We evaluated the dose reduction to the contralateral parotid by implementing standardized constraints during optimization for scanning beam proton therapy planning. METHODS Twenty-four (24) consecutive patients previously treated for base of tongue carcinoma were retrospectively selected. The doses were 70Gy, 63Gy and 57Gy (SIB in 33 fractions) for high-, intermediate-, and standard-risk clinical target volumes (CTV), respectively; the treatment included bilateral neck. Scanning beams using MFO with standardized bilateral anterior oblique and PA fields were applied. New plans where then developed and optimized by employing additional contralateral parotid constraints at multiple defined dose levels. Using a step-wise iterative process, the volume-based constraints at each level were then further reduced until known target coverages were compromised. The newly developed plans were then compared to the original clinically approved plans using paired student t-testing. RESULTS All 24 newly optimized treatment plans maintained initial plan quality as compared to the approved plans, and the 98% prescription dose coverage to the CTVs were not compromised. Representative DVH comparison is shown in FIGURE 1. The contralateral parotid doses were reduced at all levels of interest when systematic constraints were applied to V10, V20, V30 and V40Gy (All P<0.0001; TABLE 1). Overall, the mean contralateral parotid doses were reduced by 2.26 Gy on average, a ∼13% relative improvement. CONCLUSION Applying systematic and volume-based contralateral parotid constraints for IMPT planning significantly reduced the dose at all dosimetric levels for patients with base of tongue cancer.

SU-F-T-148: Are the Approximations in Analytic Semi-Empirical Dose Calculation Algorithms for Intensity Modulated Proton Therapy for Complex Heterogeneities of Head and Neck Clinically Significant?

PURPOSE Evaluate the differences in dose distributions between the proton analytic semi-empirical dose calculation algorithm used in the clinic and Monte Carlo calculations for a sample of 50 head-and-neck (H&N) patients and estimate the potential clinical significance of the differences. METHODS A cohort of 50 H&N patients, treated at the University of Texas Cancer Center with Intensity Modulated Proton Therapy (IMPT), were selected for evaluation of clinical significance of approximations in computed dose distributions. H&N site was selected because of the highly inhomogeneous nature of the anatomy. The Fast Dose Calculator (FDC), a fast track-repeating accelerated Monte Carlo algorithm for proton therapy, was utilized for the calculation of dose distributions delivered during treatment plans. Because of its short processing time, FDC allows for the processing of large cohorts of patients. FDC has been validated versus GEANT4, a full Monte Carlo system and measurements in water and for inhomogeneous phantoms. A gamma-index analysis, DVHs, EUDs, and TCP and NTCPs computed using published models were utilized to evaluate the differences between the Treatment Plan System (TPS) and FDC. RESULTS The Monte Carlo results systematically predict lower dose delivered in the target. The observed differences can be as large as 8 Gy, and should have a clinical impact. Gamma analysis also showed significant differences between both approaches, especially for the target volumes. CONCLUSION Monte Carlo calculations with fast algorithms is practical and should be considered for the clinic, at least as a treatment plan verification tool.

SU-E-T-584: Commissioning of the MC2 Monte Carlo Dose Computation Engine

PURPOSE An automated system, MC2, was developed to convert DICOM proton therapy treatment plans into a sequence MCNPX input files, and submit these to a computing cluster. MC2 converts the results into DICOM format, and any treatment planning system can import the data for comparison vs. conventional dose predictions. This work describes the data and the efforts made to validate the MC2 system against measured dose profiles and how the system was calibrated to predict the correct number of monitor units (MUs) to deliver the prescribed dose. METHODS A set of simulated lateral and longitudinal profiles was compared to data measured for commissioning purposes and during annual quality assurance efforts. Acceptance criteria were relative dose differences smaller than 3% and differences in range (in water) of less than 2 mm. For two out of three double scattering beam lines validation results were already published. Spot checks were performed to assure proper performance. For the small snout, all available measurements were used for validation vs. simulated data. To calibrate the dose per MU, the energy deposition per source proton at the center of the spread out Bragg peaks (SOBPs) was recorded for a set of SOBPs from each option. Subsequently these were then scaled to the results of dose per MU determination based on published methods. The simulations of the doses in the magnetically scanned beam line were also validated vs. measured longitudinal and lateral profiles. The source parameters were fine tuned to achieve maximum agreement with measured data. The dosimetric calibration was performed by scoring energy deposition per proton, and scaling the results to a standard dose measurement of a 10 x 10 x 10 cm3 volume irradiation using 100 MU. RESULTS All simulated data passed the acceptance criteria. CONCLUSION MC2 is fully validated and ready for clinical application.

SU‐E‐T‐523: Runtime Optimization for the Automatic Monte Carlo Dose Computation System MC2

PURPOSE Optimizing runtime of a user friendly automated Monte Carlo dose computation system for proton treatments using passively scattered and intensity modulated proton therapy plans. METHODS The MC2 code is a dose computation system based on the Monte Carlo system MCNPX, which is routinely used at the MD Anderson Cancer Center. Besides the successful implementation and use of the code, the efficiency can be optimized to minimize runtime on a cluster of LINUX servers. Based on the 3-dimensional statistical uncertainty values scored during the simulation of several test proton beams in water, we have developed an optimization procedure for the minimal number of source particles required to achieve desired statistical uncertainty inside the target volume for arbitrary patient fields. RESULTS First Monte Carlo dose calculations of proton doses in patients were provided in the timeframe of one to several days. Optimization of the initial number of source particles for each proton energy (in IMPT) or range modulator wheel rotation (in PSPT) resulted in significant decrease in computation time. CONCLUSION Current efforts focus on optimization of runtime for patient specific proton plans. Among many aspects, which include variance reduction techniques, such as using increased cell importance inside the CT volume, weight window applications and others, the focus of this effort was the minimization of the number of histories to achieve acceptable statistical uncertainties.