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Title: SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System

Abstract

Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to the dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometrymore » simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.« less

Authors:
; ; ; ; ; ;  [1];  [2]
  1. St. Jude Children’s Hospital, Memphis, TN (United States)
  2. Massachusetts General Hospital, Brookline, MA (United States)
Publication Date:
OSTI Identifier:
22642397
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; COMMISSIONING; COMPUTERIZED SIMULATION; DEPTH DOSE DISTRIBUTIONS; MONTE CARLO METHOD; PATIENTS; PLANNING; PROTON BEAMS; QUALITY ASSURANCE

Citation Formats

Moskvin, V, Pirlepesov, F, Tsiamas, P, Axente, M, Lukose, R, Zhao, L, Farr, J, and Shin, J. SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System. United States: N. p., 2016. Web. doi:10.1118/1.4956292.
Moskvin, V, Pirlepesov, F, Tsiamas, P, Axente, M, Lukose, R, Zhao, L, Farr, J, & Shin, J. SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System. United States. doi:10.1118/1.4956292.
Moskvin, V, Pirlepesov, F, Tsiamas, P, Axente, M, Lukose, R, Zhao, L, Farr, J, and Shin, J. 2016. "SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System". United States. doi:10.1118/1.4956292.
@article{osti_22642397,
title = {SU-F-T-156: Monte Carlo Simulation Using TOPAS for Synchrotron Based Proton Discrete Spot Scanning System},
author = {Moskvin, V and Pirlepesov, F and Tsiamas, P and Axente, M and Lukose, R and Zhao, L and Farr, J and Shin, J},
abstractNote = {Purpose: This study provides an overview of the design and commissioning of the Monte Carlo (MC) model of the spot-scanning proton therapy nozzle and its implementation for the patient plan simulation. Methods: The Hitachi PROBEAT V scanning nozzle was simulated based on vendor specifications using the TOPAS extension of Geant4 code. FLUKA MC simulation was also utilized to provide supporting data for the main simulation. Validation of the MC model was performed using vendor provided data and measurements collected during acceptance/commissioning of the proton therapy machine. Actual patient plans using CT based treatment geometry were simulated and compared to the dose distributions produced by the treatment planning system (Varian Eclipse 13.6), and patient quality assurance measurements. In-house MATLAB scripts are used for converting DICOM data into TOPAS input files. Results: Comparison analysis of integrated depth doses (IDDs), therapeutic ranges (R90), and spot shape/sizes at different distances from the isocenter, indicate good agreement between MC and measurements. R90 agreement is within 0.15 mm across all energy tunes. IDDs and spot shapes/sizes differences are within statistical error of simulation (less than 1.5%). The MC simulated data, validated with physical measurements, were used for the commissioning of the treatment planning system. Patient geometry simulations were conducted based on the Eclipse produced DICOM plans. Conclusion: The treatment nozzle and standard option beam model were implemented in the TOPAS framework to simulate a highly conformal discrete spot-scanning proton beam system.},
doi = {10.1118/1.4956292},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To build the model of a spot scanning proton beam for the dose calculation of a synchrotron proton therapy accelerator, which is capable of accelerating protons from 50 up to 221 MeV. Methods: The spot scanning beam nozzle is modeled using TOPAS code, a simulation tool based on Geant4.9.6. The model contained a beam pipe vacuum window, a beam profile monitor, a drift chamber, two plane-parallel ionization chambers, and a spot-position monitor consisted of a multiwire ionization chamber. A water phantom is located with its upstream surface at the isocenter plane. The initial proton beam energy and anglar deflectionmore » are modeled using a Gaussian distribution with FWHM (Full Widths at Half Maximum) deponding on its beam energy. The phase space file (PSF) on a virtual surface located at the center between the two magnets is recorded. PSF is used to analyze the pencil beam features and offset the pencil beam position. The source model parameters are verificated by fitting the simulated Result to the measurement. Results: The simulated percentage depth dose (PDD) and lateral profiles of scanning pencil beams of various incident proton energies are verificated to the measurement. Generally the distance to agreement (DTA) of Bragg peaks is less than 0.2cm. The FWHM of Gaussian anglar distribution was adjusted to fit the lateral profile difference between the simulation and the measurement to less than 2∼3cm. Conclusion: A Monte Carlo model of a spot scanning proton beam was bullt based on a synchrotron proton therapy accelerator. This scanning pencil beam model will be as a block to build the broad proton beam as a proton TPS dose verification tool.« less
  • Purpose: The purposes of this study were to validate a discrete spot scanning proton beam nozzle using the Monte Carlo (MC) code MCNPX and use the MC validated model to investigate the effects of a low-dose envelope, which surrounds the beam's central axis, on measurements of integral depth dose (IDD) profiles. Methods: An accurate model of the discrete spot scanning beam nozzle from The University of Texas M. D. Anderson Cancer Center (Houston, Texas) was developed on the basis of blueprints provided by the manufacturer of the nozzle. The authors performed simulations of single proton pencil beams of various energiesmore » using the standard multiple Coulomb scattering (MCS) algorithm within the MCNPX source code and a new MCS algorithm, which was implemented in the MCNPX source code. The MC models were validated by comparing calculated in-air and in-water lateral profiles and percentage depth dose profiles for single pencil beams with their corresponding measured values. The models were then further tested by comparing the calculated and measured three-dimensional (3-D) dose distributions. Finally, an IDD profile was calculated with different scoring radii to determine the limitations on the use of commercially available plane-parallel ionization chambers to measure IDD. Results: The distance to agreement, defined as the distance between the nearest positions of two equivalent distributions with the same value of dose, between measured and simulated ranges was within 0.13 cm for both MCS algorithms. For low and intermediate pencil beam energies, the MC simulations using the standard MCS algorithm were in better agreement with measurements. Conversely, the new MCS algorithm produced better results for high-energy single pencil beams. The IDD profile calculated with cylindrical tallies with an area equivalent to the area of the largest commercially available ionization chamber showed up to 7.8% underestimation of the integral dose in certain depths of the IDD profile. Conclusions: The authors conclude that a combination of MCS algorithms is required to accurately reproduce experimental data of single pencil beams and 3-D dose distributions for the scanning beam nozzle. In addition, the MC simulations showed that because of the low-dose envelope, ionization chambers with radii as large as 4.08 cm are insufficient to accurately measure IDD profiles for a 221.8 MeV pencil beam in the scanning beam nozzle.« less
  • Purpose: For proton radiation therapy, Monte Carlo simulation (MCS) methods are recognized as the gold-standard dose calculation approach. Although previously unrealistic due to limitations in available computing power, GPU-based applications allow MCS of proton treatment fields to be performed in routine clinical use, on time scales comparable to that of conventional pencil-beam algorithms. This study focuses on validating the results of our GPU-based code (gPMC) versus fully implemented proton therapy based MCS code (TOPAS) for clinical patient cases. Methods: Two treatment sites were selected to provide clinical cases for this study: head-and-neck cases due to anatomical geometrical complexity (air cavitiesmore » and density heterogeneities), making dose calculation very challenging, and prostate cases due to higher proton energies used and close proximity of the treatment target to sensitive organs at risk. Both gPMC and TOPAS methods were used to calculate 3-dimensional dose distributions for all patients in this study. Comparisons were performed based on target coverage indices (mean dose, V90 and D90) and gamma index distributions for 2% of the prescription dose and 2mm. Results: For seven out of eight studied cases, mean target dose, V90 and D90 differed less than 2% between TOPAS and gPMC dose distributions. Gamma index analysis for all prostate patients resulted in passing rate of more than 99% of voxels in the target. Four out of five head-neck-cases showed passing rate of gamma index for the target of more than 99%, the fifth having a gamma index passing rate of 93%. Conclusion: Our current work showed excellent agreement between our GPU-based MCS code and fully implemented proton therapy based MC code for a group of dosimetrically challenging patient cases.« less
  • Purpose: Delayed charge is a small amount of charge that is delivered to the patient after the planned irradiation is halted, which may degrade the quality of the treatment by delivering unwarranted dose to the patient. This study compares two methods for minimizing the effect of delayed charge on the dose delivered with a synchrotron based discrete spot scanning proton beam. Methods: The delivery of several treatment plans was simulated by applying a normally distributed value of delayed charge, with a mean of 0.001(SD 0.00025) MU, to each spot. Two correction methods were used to account for the delayed charge.more » Method one (CM1), which is in active clinical use, accounts for the delayed charge by adjusting the MU of the current spot based on the cumulative MU. Method two (CM2) in addition reduces the planned MU by a predicted value. Every fraction of a treatment was simulated using each method and then recomputed in the treatment planning system. The dose difference between the original plan and the sum of the simulated fractions was evaluated. Both methods were tested in a water phantom with a single beam and simple target geometry. Two separate phantom tests were performed. In one test the dose per fraction was varied from 0.5 to 2 Gy using 25 fractions per plan. In the other test the number fractions were varied from 1 to 25, using 2 Gy per fraction. Three patient plans were used to determine the effect of delayed charge on the delivered dose under realistic clinical conditions. The order of spot delivery using CM1 was investigated by randomly selecting the starting spot for each layer, and by alternating per layer the starting spot from first to last. Only discrete spot scanning was considered in this study. Results: Using the phantom setup and varying the dose per fraction, the maximum dose difference for each plan of 25 fractions was 0.37–0.39 Gy and 0.03–0.05 Gy for CM1 and CM2, respectively. While varying the total number of fractions, the maximum dose difference increased at a rate of 0.015 Gy and 0.0018 Gy per fraction for CM1 and CM2, respectively. For CM1, the largest dose difference was found at the location of the first spot in each energy layer, whereas for CM2 the difference in dose was small and showed no dependence on location. For CM1, all of the fields in the patient plans had an area where their excess dose overlapped. No such correlation was found when using CM2. Randomly selecting the starting spot reduces the maximum dose difference from 0.708 to 0.15 Gy. Alternating between first and last spot reduces the maximum dose difference from 0.708 to 0.37 Gy. In the patient plans the excess dose scaled linearly at 0.014 Gy per field per fraction for CM1 and standard delivery order. Conclusions: The predictive model CM2 is superior to a cumulative irradiation model CM1 for minimizing the effects of delayed charge, particularly when considering maximal dose discrepancies and the potential for unplanned hot-spots. This study shows that the dose discrepancy potentially scales at 0.014 Gy per field per fraction for CM1.« less
  • Purpose: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)–based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. Methods and Materials: Recently, a fast and accurate graphics processor unit (GPU)–based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LET{sub d}), which makes biological dose (BD) optimization possible. To convert from LET{sub d} to BD, a simple linear relation was assumed. By use of thismore » novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. Results: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. Conclusions: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small–tumor target patients. This optimizer will be used in an upcoming feasibility trial on LET{sub d} painting for radioresistant tumors.« less