SU‐FF‐I‐50: Whole Body and Distal Organ‐Specific Dosimetry Using Parallel SN Methods

Purpose: To create a new methodology for dose computations applicable to general medical physics applications, based upon a direct deterministic solution of the (3‐D) Boltzmann transport equation (BTE). Method and Materials: Using the multigroup discrete ordinates (S_N) deterministic method in the PENTRAN‐MP (Parallel Environment Neutral‐particle TRANsport‐Medical Physics) code system, fluxes and corresponding doses were determined for a clinical test case using a UF Series B whole‐body voxelized pediatric patient phantom. With a 90 keV planar x‐ray source, we performed two sets of transport calculations based on the same phantom model, employing both the Monte Carlo (MC) and S_N methods. S_N calculations were performed using PENTRAN, and the MCNP5 code was used for MC calculations. Post processing in the PENTRAN‐MP code system includes seamless parallel data extraction using the PENDATA code, followed by application of the 3D‐DOSE code to compute dose in each phantom voxel, with dose‐volume histograms for critical organs of interest. Results: We demonstrate that the deterministic S_N and MC solutions are, in the vicinity of the source region, completely in agreement; the largest statistical error of the MC simulation was <5%, typically averaging <2%. Moreover, the deterministic S_N method also provided globally converged results in each voxel at sites distal to the source (in ∼3 hrs on 16 processors), where the MC results on the same computing platform had significant out of field error, and would require a significantly longer running time (estimated at >2000 hrs) to produce meaningful results with an acceptable stochastic error to enable comparison with the well‐converged S_N results. Conclusions: A new methodology for 3D dose calculations has been developed based on a parallel discrete ordinates (S_N) solution of the BTE. With the proper discretization applied, the S_N method presents an accurate, fast solution yielding a complete 3‐D dose distribution without stochastic error.