Room: Exhibit Hall
Purpose: The Fast Dose Calculator (FDC), a Monte Carlo (MC) GEANT4-Based track repeating algorithm for dose calculations, is commissioned for passive scattering proton therapy (PSPT) at The University of Texas MD Anderson Cancer Center (MDACC).
Methods: The FDC uses patient independent PSPT beamline configurations, â€œoptionsâ€?, as a beam source. These options are obtained through modeling of the MDACC PSPT beamline before the patient dependent components (downstream) with Monte Carlo N-Particle eXtended Code (MCNPX). The MDACC PSPT beamline contains a moving Range Modulator Wheel (RMW). Modeling of this dynamic component is done through the superposition of individual static RMW â€œanglesâ€?. Previous work was done to calibrate the energy distribution produced by FDC, through means of calibrating the superposition as a whole. This method turned out to be inadequate for many options. Here we present an improved method which treats each angle individually. Extensive energy calibration of FDC with regards to these angles was performed. FDC energy calibration is done by assessing the gamma index of the energy deposition in a water phantom on a PSPT beamline with minimal components between FDC, the corresponding measurements taken experimentally at MDACC, as well as simulation produced by MCNPX. Additionally, the validity of the new energy calibration method is tested by comparing the results of FDC and MCNPX on a cohort of PSPT patients treated with various options.
Results: An improved FDC is commissioned and ready to use for PSPT at MDACC
Conclusion: The FDC allows for fast real-time simulation of dose. Thus far, FDC has been used for intensity modulated proton therapy (IMPT). It has been used as a tool for verification, retrospective analysis, and sometimes more accurate dose distributions. Through means of the options database and an improved energy calibration method, FDC is now available to provide these same benefits for PSPT at MDACC.
Funding Support, Disclosures, and Conflict of Interest: This work is supported by the Cancer Research and Prevention Institute of Texas (CPRIT) under contract RP160232; Rice University; and The University of Texas MD Anderson Cancer Center.
Not Applicable / None Entered.