A fast GPU-accelerated Monte Carlo engine for calculation of MLC-collimated electron fields.

BACKGROUND: Although intensity-modulated radiation therapy and volumetric arc therapy have revolutionized photon external beam therapies, the technological advances associated with electron beam therapy have fallen behind. Modern linear accelerators contain technologies that would allow for more advanced forms of electron treatments, such as beam collimation, using the conventional photon multi-leaf collimator (MLC); however, no commercial solutions exist that calculate dose from such beam delivery modes. Additionally, for clinical adoption to occur, dose calculation times would need to be on par with that of modern dose calculation algorithms. PURPOSE: This work developed a graphics processing unit (GPU)-accelerated Monte Carlo (MC) engine incorporating the Varian TrueBeam linac head geometry for a rapid calculation of electron beams collimated using the conventional photon MLC. METHODS: A compute unified device architecture framework was created for the following: (1) transport of electrons and photons through the linac head geometry, considering multiple scattering, Bremsstrahlung, Møller, Compton, and pair production interactions; (2) electron and photon propagation through the CT geometry, considering all interactions plus the photoelectric effect; and (3) secondary particle cascades through the linac head and within the CT geometry. The linac head collimating geometry was modeled according to the specifications provided by the vendor, who also provided phase-space files. The MC was benchmarked against EGSnrc/DOSXYZnrc/GEANT by simulating individual interactions with simple geometries, pencil, and square beam dose calculations in various phantoms. MC-calculated dose distributions for MLC and jaw-collimated electron fields were compared to measurements in a water phantom and with radiochromic film. RESULTS: Pencil and square beam dose distributions are in good agreement with DOSXYZnrc. Angular and spatial distributions for multiple scattering and secondary particle production in thin slab geometries are in good agreement with EGSnrc and GEANT. Dose profiles for MLC and jaw-collimated 6-20-MeV electron beams showed an average absolute difference of 1.1 and 1.9 mm for the FWHM and 80%-20% penumbra from measured profiles. Percent depth doses showed differences of <5% for as compared to measurement. The computation time on an NVIDIA Tesla V100 card was 2.5 min to achieve a dose uncertainty of <1%, which is ∼300 times faster than published results in a similar geometry using a single-CPU core. CONCLUSIONS: The GPU-based MC can quickly calculate dose for electron fields collimated using the conventional photon MLC. The fast calculation times will allow for a rapid calculation of electron fields for mixed photon and electron particle therapy.

Highly efficient and sensitive patient-specific quality assurance for spot-scanned proton therapy.

The purpose of this work was to develop an end-to-end patient-specific quality assurance (QA) technique for spot-scanned proton therapy that is more sensitive and efficient than traditional approaches. The patient-specific methodology relies on independently verifying the accuracy of the delivered proton fluence and the dose calculation in the heterogeneous patient volume. A Monte Carlo dose calculation engine, which was developed in-house, recalculates a planned dose distribution on the patient CT data set to verify the dose distribution represented by the treatment planning system. The plan is then delivered in a pre-treatment setting and logs of spot position and dose monitors, which are integrated into the treatment nozzle, are recorded. A computational routine compares the delivery log to the DICOM spot map used by the Monte Carlo calculation to ensure that the delivered parameters at the machine match the calculated plan. Measurements of dose planes using independent detector arrays, which historically are the standard approach to patient-specific QA, are not performed for every patient. The nozzle-integrated detectors are rigorously validated using independent detectors in regular QA intervals. The measured data are compared to the expected delivery patterns. The dose monitor reading deviations are reported in a histogram, while the spot position discrepancies are plotted vs. spot number to facilitate independent analysis of both random and systematic deviations. Action thresholds are linked to accuracy of the commissioned delivery system. Even when plan delivery is acceptable, the Monte Carlo second check system has identified dose calculation issues which would not have been illuminated using traditional, phantom-based measurement techniques. The efficiency and sensitivity of our patient-specific QA program has been improved by implementing a procedure which independently verifies patient dose calculation accuracy and plan delivery fidelity. Such an approach to QA requires holistic integration and maintenance of patient-specific and patient-independent QA.

A linear relationship for the LET-dependence of Gafchromic EBT3 film in spot-scanning proton therapy.

Radiochromic film (RCF) is a valuable dosimetric tool, primarily due to its sub-millimeter spatial resolution. For accurate proton dosimetry, the dependence of film response on linear energy transfer (LET) must be characterized and calibrated. In this work, we characterized film under-response, or 'quenching', as a function of dose-weighted linear energy transfer (LETd) in several proton fields and established a simple, linear relationship with LETd. We performed measurements as a function of depth in a PMMA phantom irradiated by a spot-scanning proton beam. The fields had energies of 71.3 MeV, 71.3 MeV with filter, and 159.9 MeV. At each depth (measurements taken in depth step sizes of 0.5-1 mm in the Bragg peak), we measured dose with a PTW Markus ion chamber and EBT3 RCF. EBT3 under-response was characterized by the ratio of dose measured with film to that with ion chamber. LETd values for our experimental setup were calculated using in-house clinical Monte Carlo code. Measured film under-response increased with LETd, from approximately 10% under-response for LETd = 5 keV µm-1 to approximately 20% for LETd = 8 keV µm-1. The under-response for all measurements was plotted versus LETd. A linear fit to the data was performed, yielding a function for under-response, [Formula: see text], with respect to LETd: [Formula: see text]. Finally, the linear under-response relationship was applied to a film measurement within a spread-out Bragg peak (SOBP). Without correcting for LETd-dependence in the SOBP measurement, the discrepancy between film and Monte Carlo profiles was greater than 15% at the distal edge. With correction, the corrected film profile was within 2% and 1 mm of the Monte Carlo profile. RCF response depends on LETd, potentially under-responding by >15% in clinically-relevant scenarios. Therefore, it is insufficient to perform only a dose calibration; LET calibration is also necessary for accurate proton film dosimetry. The LETd-dependence of EBT3 can be described by a single, linear function over a range of clinically-relevant proton therapy LETd values.

A fast GPU-based Monte Carlo simulation of proton transport with detailed modeling of nonelastic interactions.

PURPOSE: Very fast Monte Carlo (MC) simulations of proton transport have been implemented recently on graphics processing units (GPUs). However, these MCs usually use simplified models for nonelastic proton-nucleus interactions. Our primary goal is to build a GPU-based proton transport MC with detailed modeling of elastic and nonelastic proton-nucleus collisions. METHODS: Using the cuda framework, the authors implemented GPU kernels for the following tasks: (1) simulation of beam spots from our possible scanning nozzle configurations, (2) proton propagation through CT geometry, taking into account nuclear elastic scattering, multiple scattering, and energy loss straggling, (3) modeling of the intranuclear cascade stage of nonelastic interactions when they occur, (4) simulation of nuclear evaporation, and (5) statistical error estimates on the dose. To validate our MC, the authors performed (1) secondary particle yield calculations in proton collisions with therapeutically relevant nuclei, (2) dose calculations in homogeneous phantoms, (3) recalculations of complex head and neck treatment plans from a commercially available treatment planning system, and compared with (GEANT)4.9.6p2/TOPAS. RESULTS: Yields, energy, and angular distributions of secondaries from nonelastic collisions on various nuclei are in good agreement with the (GEANT)4.9.6p2 Bertini and Binary cascade models. The 3D-gamma pass rate at 2%-2 mm for treatment plan simulations is typically 98%. The net computational time on a NVIDIA GTX680 card, including all CPU-GPU data transfers, is ∼ 20 s for 1 × 10(7) proton histories. CONCLUSIONS: Our GPU-based MC is the first of its kind to include a detailed nuclear model to handle nonelastic interactions of protons with any nucleus. Dosimetric calculations are in very good agreement with (GEANT)4.9.6p2/TOPAS. Our MC is being integrated into a framework to perform fast routine clinical QA of pencil-beam based treatment plans, and is being used as the dose calculation engine in a clinically applicable MC-based IMPT treatment planning system. The detailed nuclear modeling will allow us to perform very fast linear energy transfer and neutron dose estimates on the GPU.