title: An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.
abstract: Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum dose difference within 1.7%. The maximum relative difference of output factors was within 0.5%. Over 98.5% passing rate was achieved in 3D gamma-index tests with 2%/2 mm criteria in both an IMRT prostate patient case and a head-and-neck case. These results demonstrated the efficacy of our model in terms of accurately representing a reference phase-space file. We have also tested the efficiency gain of our source model over our previously developed phase-space-let file source model. The overall efficiency of dose calculation was found to be improved by ~1.3-2.2 times in water and patient cases using our analytical model.
authors.affiliation: Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Tian
authors.forename: Yongbao
authors.initials: Y
authors.lastname: Li
authors.forename: Michael
authors.initials: M
authors.lastname: Folkerts
authors.forename: Feng
authors.initials: F
authors.lastname: Shi
authors.forename: Steve B
authors.initials: SB
authors.lastname: Jiang
authors.forename: Xun
authors.initials: X
authors.lastname: Jia
mesh_terms: D003198:Computer Simulation; D017076:Computer-Aided Design; D004583:Electrons; D006258:Head and Neck Neoplasms / Q000532:radiotherapy; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D010315:Particle Accelerators / Q000295:instrumentation*; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000532:radiotherapy; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated; D012984:Software