TH‐EF‐BRA‐02: Patient‐Specific Dose Maps for CT Scans Using a Fast, Deterministic Boltzmann Transport Equation Solver

Abstract

Purpose: To develop a rapid and accurate software tool for computing patient‐specific radiation dose maps of dose delivered from kV computed tomography (CT) scans. Methods: Monte Carlo methods currently provide the gold‐standard for calculating patient‐specific dose maps, but require immense computational resources to achieve sufficiently high statistical accuracy. To overcome this limitation, a deterministic method was implemented to solve the same underlying Boltzmann transport equation (BTE) that governs particle interactions and transport. Phase‐space was discretized according to spatial location, energy, and angle, and a deterministic finite element algorithm was applied to compute the object's photon fluence distribution, which does not exhibit stochastic noise. A computationally efficient GPU implementation for a standard workstation was developed, and comparison was made between the performance of the deterministic BTE solver and a standard Monte Carlo algorithm for a cone‐beam projection of a virtual anthropomorphic chest phantom. Results: The BTE solution and Monte Carlo results were in strong agreement with a relative root‐mean square error (RMSE) of 3.47%. Some larger differences existed at high‐contrast boundaries (e.g., air/water) and within the bone, and are under further investigation. Notably, the computation time of the BTE solver was 8 seconds, while to obtain the same level of statistical uncertainty with conventional Monte Carlo required 1200 CPU‐hours. Additionally, unlike Monte Carlo, the BTE computation time is only weakly dependent on the number of sources, making it extremely well‐suited for CT dose calculations. Therefore, the BTE‐based method is expected to offer a >30,000x speed increase compared to Monte Carlo for entire CT scans, even after application of variance reduction techniques and GPU implementation. Conclusion: The novel deterministic BTE solver offers a significantly faster alternative to Monte Carlo‐based methods for computing dose delivered by CT scans, which can enable estimation of patient‐specific organ doses for each CT examination performed. Adam Wang, Alex Maslowski, Todd Wareing, and Josh Star‐Lack are employees of Varian Medical Systems.

AcurosCTS: A fast, linear Boltzmann transport equation solver for computed tomography scatter – Part I: Core algorithms and validation

“…Once the angular fluence distribution is calculated, we can convert to dose delivered by using the mass density and mass energy‐absorption coefficient of each voxel, which is simply a property of its materials. While the full details of our preliminary dose study are beyond the scope of this paper, the Acuros CTS results showed excellent agreement with Geant4 simulations . We anticipate being able to use Acuros CTS to compute dose from a cone‐beam CT scan or for diagnostic CT scans, where there is great interest in better dose reporting …”

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm

“…Acuros CT-Dose is currently a research tool and not available for commercial use) to rapidly compute the dose maps. 22 Alternatively, many groups have investigated graphics processing unitbased Monte Carlo simulation for accelerated computation of dose maps. 23,24 This study investigates the feasibility of the second step of the process-automated segmentation-as required to compute individual organ doses.…”

Accuracy of patient specific organ-dose estimates obtained using an automated image segmentation algorithm

“…Acuros CTDose is currently a research tool and not available for commercial use) to rapidly compute the dose maps. 22 Alternatively, many groups have investigated graphics processing unitbased Monte Carlo simulation for accelerated computation of dose maps. 23,24 This study investigates the feasibility of the second step of the process-automated segmentation-as required to compute individual organ doses.…”