title: Validation of a GPU-based Monte Carlo code (gPMC) for proton radiation therapy: clinical cases study.
abstract: 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.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
authors.forename: Drosoula
authors.initials: D
authors.lastname: Giantsoudi
authors.forename: Jan
authors.initials: J
authors.lastname: Schuemann
authors.forename: Xun
authors.initials: X
authors.lastname: Jia
authors.forename: Stephen
authors.initials: S
authors.lastname: Dowdell
authors.forename: Steve
authors.initials: S
authors.lastname: Jiang
authors.forename: Harald
authors.initials: H
authors.lastname: Paganetti
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D009369:Neoplasms / Q000175:diagnosis / Q000532:radiotherapy*; D061766:Proton Therapy / Q000379:methods*; D011522:Protons; D011834:Radiation Monitoring / Q000379:methods*; D011879:Radiotherapy Dosage
chemical_list: D011522:Protons