Can differences in linear energy transfer and thus relative biological effectiveness compromise the dosimetric advantage of intensity-modulated proton therapy as compared to passively scattered proton therapy?

PURPOSE: To investigate the effect of differences in linear energy transfer (LET) and thus the relative biological effectiveness (RBE) between passively scattered proton therapy (PS) and pencil-beam scanning intensity-modulated proton therapy (IMPT). METHODS: IMPT treatment plans were generated for six ependymoma patients, originally treated with PS, using the original plan's computed tomography image sets and beam directions, and its dose-volume values as optimization constraints. Two beam spot sizes and both single-field optimization (SFO) and multi-field optimization (MFO) techniques were used for each patient. Three-dimensional variable-RBE-weighted dose distributions were computed, using Monte Carlo calculated dose and LET distributions, and a linear dose and LET-based RBE model, and were compared between the two delivery methods. RESULTS: Increased target dose coverage and decreased mean and maximum dose to the OARs was achieved with IMPT compared to PS, for constant RBE value of 1.1. Nevertheless, the maximum variable-RBE-weighted dose to the brainstem, was increased up to 6% for the IMPT plans compared to the corresponding PS plans. CONCLUSIONS: IMPT can be dosimetrically superior to PS for ependymoma patients. However, caution should be exercised so that the increased dose conformity is not counteracted by an increase in radiobiological effect in adjacent critical structures.

Evaluating Intensity Modulated Proton Therapy Relative to Passive Scattering Proton Therapy for Increased Vertebral Column Sparing in Craniospinal Irradiation in Growing Pediatric Patients.

PURPOSE: At present, proton craniospinal irradiation (CSI) for growing children is delivered to the whole vertebral body (WVB) to avoid asymmetric growth. We aimed to demonstrate the feasibility and potential clinical benefit of delivering vertebral body sparing (VBS) versus WVB CSI with passively scattered (PS) and intensity modulated proton therapy (IMPT) in growing children treated for medulloblastoma. METHODS AND MATERIALS: Five plans were generated for medulloblastoma patients, who had been previously treated with CSI PS proton radiation therapy: (1) single posteroanterior (PA) PS field covering the WVB (PS-PA-WVB); (2) single PA PS field that included only the thecal sac in the target volume (PS-PA-VBS); (3) single PA IMPT field covering the WVB (IMPT-PA-WVB); (4) single PA IMPT field, target volume including thecal sac only (IMPT-PA-VBS); and (5) 2 posterior-oblique (-35°, +35°) IMPT fields, with the target volume including the thecal sac only (IMPT2F-VBS). For all cases, 23.4 Gy (relative biologic effectiveness [RBE]) was prescribed to 95% of the spinal canal. The dose, linear energy transfer, and variable-RBE-weighted dose distributions were calculated for all plans using the tool for particle simulation, version 2, Monte Carlo system. RESULTS: IMPT VBS techniques efficiently spared the anterior vertebral bodies (AVBs), even when accounting for potential higher variable RBE predicted by linear energy transfer distributions. Assuming an RBE of 1.1, the V10 Gy(RBE) decreased from 100% for the WVB techniques to 59.5% to 76.8% for the cervical, 29.9% to 34.6% for the thoracic, and 20.6% to 25.1% for the lumbar AVBs, and the V20 Gy(RBE) decreased from 99.0% to 17.8% to 20.0% for the cervical, 7.2% to 7.6% for the thoracic, and 4.0% to 4.6% for the lumbar AVBs when IMPT VBS techniques were applied. The corresponding percentages for the PS VBS technique were higher. CONCLUSIONS: Advanced proton techniques can sufficiently reduce the dose to the vertebral body and allow for vertebral column growth for children with central nervous system tumors requiring CSI. This was true even when considering variable RBE values. A clinical trial is planned for VBS to the thoracic and lumbosacral spine in growing children.

Proton Treatment Techniques for Posterior Fossa Tumors: Consequences for Linear Energy Transfer and Dose-Volume Parameters for the Brainstem and Organs at Risk.

PURPOSE: In proton therapy of posterior fossa tumors, at least partial inclusion of the brainstem in the target is necessary because of its proximity to the tumor and required margins. Additionally, the preferred beam geometry results in directing the field distal edge toward this critical structure, raising concerns for brainstem toxicity. Some treatment techniques place the beam's distal edge within the brainstem (dose-sparing techniques), and others avoid elevated linear energy transfer (LET) of the proton field by placing the distal edge beyond it (LET-sparing techniques). Hybrid approaches are also being used. We examine the dosimetric efficacy of these techniques, accounting for LET-dependent and dose-dependent variable relative biologic effectiveness (RBE) distributions. METHODS: Six techniques were applied in ependymoma cases: (a) 3-field dose-sparing; (b) 3-field LET-sparing; (c) 2-field dose-sparing, wide angles; (d) 2-field LET-sparing, wide angles; (e) 2-field LET-sparing, steep angles; and (f) 2-field LET-sparing with feathered distal end. Monte Carlo calculated dose, LET, and RBE-weighted dose distributions were compared. RESULTS: Decreased LET values in the brainstem by LET-sparing techniques were accompanied by higher, not statistically significant, median dose: 53.6 Gy(RBE), 53.4 Gy(RBE), and 54.3 Gy(RBE) for techniques (b), (d), and (e) versus 52.1 Gy(RBE) for technique (a). Accounting for variable RBE distributions, the brainstem volume receiving at least 55 Gy(RBE) increased from 72.5% for technique (a) to 80.3% for (b) (P<.01) and from 70.7% for technique (c) to 77.6% for (d) (P<.01). Less than 2%, but statistically significant, decrease in maximum variable RBE-weighted brainstem dose was observed for the LET-sparing techniques compared with the corresponding dose-sparing (P=.03 and .004). CONCLUSIONS: Extending the proton range beyond the brainstem to reduce LET results in clinically comparable maximum radiobiologic effective dose to this sensitive structure. However this method significantly increasing the brainstem volume receiving RBE-weighted dose higher than 55 Gy(RBE) with possible consequences based on known dose-volume parameters for increased toxicity.

Reoptimization of Intensity Modulated Proton Therapy Plans Based on Linear Energy Transfer.

PURPOSE: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution. METHODS AND MATERIALS: To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET. RESULTS: The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives. CONCLUSION: LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.

Recent developments and comprehensive evaluations of a GPU-based Monte Carlo package for proton therapy.

Monte Carlo (MC) simulation is commonly considered as the most accurate dose calculation method for proton therapy. Aiming at achieving fast MC dose calculations for clinical applications, we have previously developed a graphics-processing unit (GPU)-based MC tool, gPMC. In this paper, we report our recent updates on gPMC in terms of its accuracy, portability, and functionality, as well as comprehensive tests on this tool. The new version, gPMC v2.0, was developed under the OpenCL environment to enable portability across different computational platforms. Physics models of nuclear interactions were refined to improve calculation accuracy. Scoring functions of gPMC were expanded to enable tallying particle fluence, dose deposited by different particle types, and dose-averaged linear energy transfer (LETd). A multiple counter approach was employed to improve efficiency by reducing the frequency of memory writing conflict at scoring. For dose calculation, accuracy improvements over gPMC v1.0 were observed in both water phantom cases and a patient case. For a prostate cancer case planned using high-energy proton beams, dose discrepancies in beam entrance and target region seen in gPMC v1.0 with respect to the gold standard tool for proton Monte Carlo simulations (TOPAS) results were substantially reduced and gamma test passing rate (1%/1 mm) was improved from 82.7%-93.1%. The average relative difference in LETd between gPMC and TOPAS was 1.7%. The average relative differences in the dose deposited by primary, secondary, and other heavier particles were within 2.3%, 0.4%, and 0.2%. Depending on source proton energy and phantom complexity, it took 8-17 s on an AMD Radeon R9 290x GPU to simulate [Formula: see text] source protons, achieving less than [Formula: see text] average statistical uncertainty. As the beam size was reduced from 10 × 10 cm2 to 1 × 1 cm2, the time on scoring was only increased by 4.8% with eight counters, in contrast to a 40% increase using only one counter. With the OpenCL environment, the portability of gPMC v2.0 was enhanced. It was successfully executed on different CPUs and GPUs and its performance on different devices varied depending on processing power and hardware structure.

Can We Advance Proton Therapy for Prostate? Considering Alternative Beam Angles and Relative Biological Effectiveness Variations When Comparing Against Intensity Modulated Radiation Therapy.

PURPOSE: For prostate treatments, robust evidence regarding the superiority of either intensity modulated radiation therapy (IMRT) or proton therapy is currently lacking. In this study we investigated the circumstances under which proton therapy should be expected to outperform IMRT, particularly the proton beam orientations and relative biological effectiveness (RBE) assumptions. METHODS AND MATERIALS: For 8 patients, 4 treatment planning strategies were considered: (A) IMRT; (B) passively scattered standard bilateral (SB) proton beams; (C) passively scattered anterior oblique (AO) proton beams, and (D) AO intensity modulated proton therapy (IMPT). For modalities (B)-(D) the dose and linear energy transfer (LET) distributions were simulated using the TOPAS Monte Carlo platform and RBE was calculated according to 3 different models. RESULTS: Assuming a fixed RBE of 1.1, our implementation of IMRT outperformed SB proton therapy across most normal tissue metrics. For the scattered AO proton plans, application of the variable RBE models resulted in substantial hotspots in rectal RBE weighted dose. For AO IMPT, it was typically not possible to find a plan that simultaneously met the tumor and rectal constraints for both fixed and variable RBE models. CONCLUSION: If either a fixed RBE of 1.1 or a variable RBE model could be validated in vivo, then it would always be possible to use AO IMPT to dose-boost the prostate and improve normal tissue sparing relative to IMRT. For a cohort without rectum spacer gels, this study (1) underlines the importance of resolving the question of proton RBE within the framework of an IMRT versus proton debate for the prostate and (2) highlights that without further LET/RBE model validation, great care must be taken if AO proton fields are to be considered for prostate treatments.

Incidence of CNS Injury for a Cohort of 111 Patients Treated With Proton Therapy for Medulloblastoma: LET and RBE Associations for Areas of Injury.

BACKGROUND: Central nervous system (CNS) injury is a rare complication of radiation therapy for pediatric brain tumors, but its incidence with proton radiation therapy (PRT) is less well defined. Increased linear energy transfer (LET) and relative biological effectiveness (RBE) at the distal end of proton beams may influence this risk. We report the incidence of CNS injury in medulloblastoma patients treated with PRT and investigate correlations with LET and RBE values. METHODS AND MATERIALS: We reviewed 111 consecutive patients treated with PRT for medulloblastoma between 2002 and 2011 and selected patients with clinical symptoms of CNS injury. Magnetic resonance imaging (MRI) findings for all patients were contoured on original planning scans (treatment change areas [TCA]). Dose and LET distributions were calculated for the treated plans using Monte Carlo system. RBE values were estimated based on LET-based published models. RESULTS: At a median follow-up of 4.2 years, the 5-year cumulative incidence of CNS injury was 3.6% for any grade and 2.7% for grade 3+. Three of 4 symptomatic patients were treated with a whole posterior fossa boost. Eight of 10 defined TCAs had higher LET values than the target but statistically nonsignificant differences in RBE values (P=.12). CONCLUSIONS: Central nervous system and brainstem injury incidence for PRT in this series is similar to that reported for photon radiation therapy. The risk of CNS injury was higher for whole posterior fossa boost than for involved field. Although no clear correlation with RBE values was found, numbers were small and additional investigation is warranted to better determine the relationship between injury and LET.

Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy.

PURPOSE: To assess the impact of approximations in current analytical dose calculation methods (ADCs) on tumor control probability (TCP) in proton therapy. METHODS: Dose distributions planned with ADC were compared with delivered dose distributions as determined by Monte Carlo simulations. A total of 50 patients were investigated in this analysis with 10 patients per site for 5 treatment sites (head and neck, lung, breast, prostate, liver). Differences were evaluated using dosimetric indices based on a dose-volume histogram analysis, a γ-index analysis, and estimations of TCP. RESULTS: We found that ADC overestimated the target doses on average by 1% to 2% for all patients considered. The mean dose, D95, D50, and D02 (the dose value covering 95%, 50% and 2% of the target volume, respectively) were predicted within 5% of the delivered dose. The γ-index passing rate for target volumes was above 96% for a 3%/3 mm criterion. Differences in TCP were up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head and neck, and lung patients, respectively. Differences in normal tissue complication probabilities for bladder and anterior rectum of prostate patients were less than 3%. CONCLUSION: Our results indicate that current dose calculation algorithms lead to underdosage of the target by as much as 5%, resulting in differences in TCP of up to 11%. To ensure full target coverage, advanced dose calculation methods like Monte Carlo simulations may be necessary in proton therapy. Monte Carlo simulations may also be required to avoid biases resulting from systematic discrepancies in calculated dose distributions for clinical trials comparing proton therapy with conventional radiation therapy.

Validation of a GPU-based Monte Carlo code (gPMC) for proton radiation therapy: clinical cases study.

Monte Carlo (MC) methods are recognized as the gold-standard for dose calculation, however they have not replaced analytical methods up to now due to their lengthy calculation times. GPU-based applications allow MC dose calculations to be performed on time scales comparable to conventional analytical algorithms. This study focuses on validating our GPU-based MC code for proton dose calculation (gPMC) using an experimentally validated multi-purpose MC code (TOPAS) and compare their performance for clinical patient cases. Clinical cases from five treatment sites were selected covering the full range from very homogeneous patient geometries (liver) to patients with high geometrical complexity (air cavities and density heterogeneities in head-and-neck and lung patients) and from short beam range (breast) to large beam range (prostate). Both gPMC and TOPAS were used to calculate 3D dose distributions for all patients. Comparisons were performed based on target coverage indices (mean dose, V95, D98, D50, D02) and gamma index distributions. Dosimetric indices differed less than 2% between TOPAS and gPMC dose distributions for most cases. Gamma index analysis with 1%/1 mm criterion resulted in a passing rate of more than 94% of all patient voxels receiving more than 10% of the mean target dose, for all patients except for prostate cases. Although clinically insignificant, gPMC resulted in systematic underestimation of target dose for prostate cases by 1-2% compared to TOPAS. Correspondingly the gamma index analysis with 1%/1 mm criterion failed for most beams for this site, while for 2%/1 mm criterion passing rates of more than 94.6% of all patient voxels were observed. For the same initial number of simulated particles, calculation time for a single beam for a typical head and neck patient plan decreased from 4 CPU hours per million particles (2.8-2.9 GHz Intel X5600) for TOPAS to 2.4 s per million particles (NVIDIA TESLA C2075) for gPMC. Excellent agreement was demonstrated between our fast GPU-based MC code (gPMC) and a previously extensively validated multi-purpose MC code (TOPAS) for a comprehensive set of clinical patient cases. This shows that MC dose calculations in proton therapy can be performed on time scales comparable to analytical algorithms with accuracy comparable to state-of-the-art CPU-based MC codes.

Patterns of failure after proton therapy in medulloblastoma; linear energy transfer distributions and relative biological effectiveness associations for relapses.

PURPOSE: The pattern of failure in medulloblastoma patients treated with proton radiation therapy is unknown. For this increasingly used modality, it is important to ensure that outcomes are comparable to those in modern photon series. It has been suggested this pattern may differ from photons because of variations in linear energy transfer (LET) and relative biological effectiveness (RBE). In addition, the use of matching fields for delivery of craniospinal irradiation (CSI) may influence patterns of relapse. Here we report the patterns of failure after the use of protons, compare it to that in the available photon literature, and determine the LET and RBE values in areas of recurrence. METHODS AND MATERIALS: Retrospective review of patients with medulloblastoma treated with proton radiation therapy at Massachusetts General Hospital (MGH) between 2002 and 2011. We documented the locations of first relapse. Discrete failures were contoured on the original planning computed tomography scan. Monte Carlo calculation methods were used to estimate the proton LET distribution. Models were used to estimate RBE values based on the LET distributions. RESULTS: A total of 109 patients were followed for a median of 38.8 months (range, 1.4-119.2 months). Of the patients, 16 experienced relapse. Relapse involved the supratentorial compartment (n=8), spinal compartment (n=11), and posterior fossa (n=5). Eleven failures were isolated to a single compartment; 6 failures in the spine, 4 failures in the supratentorium, and 1 failure in the posterior fossa. The remaining patients had multiple sites of disease. One isolated spinal failure occurred at the spinal junction of 2 fields. None of the 70 patients treated with an involved-field-only boost failed in the posterior fossa outside of the tumor bed. We found no correlation between Monte Carlo-calculated LET distribution and regions of recurrence. CONCLUSIONS: The most common site of failure in patients treated with protons for medulloblastoma was outside of the posterior fossa. The most common site for isolated local failure was the spine. We recommend consideration of spinal imaging in follow-up and careful attention to dose distribution in the spinal junction regions. Development of techniques that do not require field matching may be of benefit. We did not identify a direct correlation between lower LET values and recurrence in medulloblastoma patients treated with proton therapy. Patterns of failure do not appear to differ from those in patients treated with photon therapy.

Linear energy transfer-guided optimization in intensity modulated proton therapy: feasibility study and clinical potential.

PURPOSE: To investigate the feasibility and potential clinical benefit of linear energy transfer (LET) guided plan optimization in intensity modulated proton therapy (IMPT). METHODS AND MATERIALS: A multicriteria optimization (MCO) module was used to generate a series of Pareto-optimal IMPT base plans (BPs), corresponding to defined objectives, for 5 patients with head-and-neck cancer and 2 with pancreatic cancer. A Monte Carlo platform was used to calculate dose and LET distributions for each BP. A custom-designed MCO navigation module allowed the user to interpolate between BPs to produce deliverable Pareto-optimal solutions. Differences among the BPs were evaluated for each patient, based on dose-volume and LET-volume histograms and 3-dimensional distributions. An LET-based relative biological effectiveness (RBE) model was used to evaluate the potential clinical benefit when navigating the space of Pareto-optimal BPs. RESULTS: The mean LET values for the target varied up to 30% among the BPs for the head-and-neck patients and up to 14% for the pancreatic cancer patients. Variations were more prominent in organs at risk (OARs), where mean LET values differed by a factor of up to 2 among the BPs for the same patient. An inverse relation between dose and LET distributions for the OARs was typically observed. Accounting for LET-dependent variable RBE values, a potential improvement on RBE-weighted dose of up to 40%, averaged over several structures under study, was noticed during MCO navigation. CONCLUSIONS: We present a novel strategy for optimizing proton therapy to maximize dose-averaged LET in tumor targets while simultaneously minimizing dose-averaged LET in normal tissue structures. MCO BPs show substantial LET variations, leading to potentially significant differences in RBE-weighted doses. Pareto-surface navigation, using both dose and LET distributions for guidance, provides the means for evaluating a large variety of deliverable plans and aids in identifying the clinically optimal solution.