[en] Purpose: To develop a clinically applicable intensity modulated proton therapy (IMPT) optimization system that utilizes more accurate Monte Carlo (MC) dose calculation, rather than analytical dose calculation. Methods: A very fast 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 gradient based optimization method was used to achieve the desired dose volume histograms (DVH). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve the spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that Result from maintaining the intrinsic CT resolution and large number of proton spots. The dose effects were studied particularly in cases with heterogeneous materials in comparison with the commercial treatment planning system (TPS). Results: For a relatively large and complex three-field bi-lateral head and neck case (i.e. >100K spots with a target volume of ∼1000 cc and multiple surrounding critical structures), the optimization together with the initial MC dose influence map calculation can be done in a clinically viable time frame (i.e. less than 15 minutes) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The DVHs of the MC TPS plan compare favorably with those of a commercial treatment planning system. Conclusion: A GPU accelerated and MC-based IMPT optimization system was developed. The dose calculation and plan optimization can be performed in less than 15 minutes on a hardware system costing less than 45,000 dollars. The fast calculation and optimization makes the system easily expandable to robust and multi-criteria optimization. This work was funded in part by a grant from Varian Medical Systems, Inc

[en] Purpose: To build a GPU-based Monte Carlo (MC) simulation of proton transport with detailed modeling of elastic and non-elastic (NE) protonnucleus interactions, for use in a very fast and cost-effective proton therapy treatment plan verification system. Methods: Using the CUDA framework, we implemented 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 and multiple scattering, as well as energy straggling, (3) Bertini-style modeling of the intranuclear cascade stage of NE interactions, and (4) Simulation of nuclear evaporation. To validate our MC, we performed: (1) Secondary particle yield calculations in NE collisions with therapeutically-relevant nuclei, (2) Pencil-beam dose calculations in homogeneous phantoms, (3) A large number of treatment plan dose recalculations, and compared with Geant4.9.6p2/TOPAS. A workflow was devised for calculating plans from a commercially available treatment planning system, with scripts for reading DICOM files and generating inputs for our MC. Results: Yields, energy and angular distributions of secondaries from NE collisions on various nuclei are in good agreement with the Geant4.9.6p2 Bertini and Binary cascade models. The 3D-gamma pass rate at 2%–2mm for 70–230 MeV pencil-beam dose distributions in water, soft tissue, bone and Ti phantoms is 100%. The pass rate at 2%–2mm for treatment plan calculations is typically above 98%. The net computational time on a NVIDIA GTX680 card, including all CPU-GPU data transfers, is around 20s for 1×10⁷ proton histories. Conclusion: Our GPU-based proton transport MC is the first of its kind to include a detailed nuclear model to handle NE interactions on any nucleus. Dosimetric calculations demonstrate very good agreement with Geant4.9.6p2/TOPAS. Our MC is being integrated into a framework to perform fast routine clinical QA of pencil-beam treatment plans. Hardware for such a system will cost under $5000. This work was funded in part by a grant from Varian Medical Systems, Inc

[en] Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) based biological planning for the treatment of thyroid tumors in spot-scanning proton therapy. Methods: Recently, we developed a fast and accurate GPU-based MC simulation of proton transport that was benchmarked against Geant4.9.6 and used as the dose calculation engine in a clinically-applicable GPU-accelerated IMPT optimizer. Besides dose, it can simultaneously score the dose-averaged LET (LETd), which makes fast biological dose (BD) estimates possible. To convert from LETd to BD, we used a linear relation based on cellular irradiation data. Given a thyroid patient with a 93cc tumor volume, we created a 2-field IMPT plan in Eclipse (Varian Medical Systems). This plan was re-calculated with our MC to obtain the BD distribution. A second 5-field plan was made with our in-house optimizer, using pre-generated MC dose and LETd maps. Constraints were placed to maintain the target dose to within 25% of the prescription, while maximizing the BD. The plan optimization and calculation of dose and LETd maps were performed on a GPU cluster. The conventional IMPT and biologically-optimized plans were compared. Results: The mean target physical and biological doses from our biologically-optimized plan were, respectively, 5% and 14% higher than those from the MC re-calculation of the IMPT plan. Dose sparing to critical structures in our plan was also improved. The biological optimization, including the initial dose and LETd map calculations, can be completed in a clinically viable time (∼30 minutes) on a cluster of 25 GPUs. Conclusion: Taking advantage of GPU acceleration, we created a MC-based, biologically optimized treatment plan for a thyroid patient. Compared to a standard IMPT plan, a 5% increase in the target’s physical dose resulted in ∼3 times as much increase in the BD. Biological planning was thus effective in escalating the target BD

[en] We report on ellipsometric measurements of the refractive indices of linear alkylbenzene-2,5-diphenyloxazole (LAB-PPO), Nd-doped LAB-PPO and EJ-301 scintillators to the nearest ± 0.005, in the wavelength range 210-1000 nm.

[en] 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 (LET_d) in several proton fields and established a simple, linear relationship with LET_d.

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. LET_d values for our experimental setup were calculated using in-house clinical Monte Carlo code. Measured film under-response increased with LET_d, from approximately 10% under-response for LET_d  =  5 keV µm⁻¹ to approximately 20% for LET_d  =  8 keV µm⁻¹. The under-response for all measurements was plotted versus LET_d. A linear fit to the data was performed, yielding a function for under-response, , with respect to LET_d: . Finally, the linear under-response relationship was applied to a film measurement within a spread-out Bragg peak (SOBP). Without correcting for LET_d-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 LET_d, 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 LET_d-dependence of EBT3 can be described by a single, linear function over a range of clinically-relevant proton therapy LET_d values. (paper)

[en] An experimental test of the electron energy scale linearities of SNO+ and EJ-301 scintillators was carried out using a Compton spectrometer with electrons in the energy range 0.09-3 MeV. The linearity of the apparatus was explicitly demonstrated. It was found that the response of both types of scintillators with respect to electrons becomes non-linear below ∼0.4MeV. An explanation is given in terms of Cherenkov light absorption and re-emission by the scintillators.

No abstract available

[en] A search has been made for neutrinos from the hep reaction in the Sun and from the diffuse supernova neutrino background (DSNB)using data collected during the first operational phase of the Sudbury Neutrino Observatory, with an exposure of 0.65 kilotons-years. For the hep neutrino search, two events are observed in the effective electron energy range of 14.3 MeV< T_eff<20 MeV where 3.1 background events are expected. After accounting for neutrino oscillations, an upper limit of 2.3 x 104 cm-2s-1 at the 90 percent confidence level is inferred on the integral total flux of hep neutrinos. For DSNB neutrinos, no events are observed in the effective electron energy range of 21 MeV< T_eff<35 MeV and, consequently, an upper limit on the nu e component of the DSNB flux in the neutrino energy range of 22.9 MeV< E nu<36.9 MeV of 70 cm-2-1 is inferred at the 90 percent confidence level. This is an improvement by a factor of 6.5 on the previous best upper limit on the hep neutrino flux and by two orders of magnitude on the previous upper limit on the nu e component of the DSNB flux