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Title: SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation

Abstract

Purpose: Monte Carlo (MC) simulation is an important tool to solve radiotherapy and medical imaging problems. Low computational efficiency hinders its wide applications. Conventionally, MC is performed in a particle-by -particle fashion. The lack of control on particle trajectory is a main cause of low efficiency in some applications. Take cone beam CT (CBCT) projection simulation as an example, significant amount of computations were wasted on transporting photons that do not reach the detector. To solve this problem, we propose an innovative MC simulation scheme with a path-by-path sampling method. Methods: Consider a photon path starting at the x-ray source. After going through a set of interactions, it ends at the detector. In the proposed scheme, we sampled an entire photon path each time. Metropolis-Hasting algorithm was employed to accept/reject a sampled path based on a calculated acceptance probability, in order to maintain correct relative probabilities among different paths, which are governed by photon transport physics. We developed a package gMMC on GPU with this new scheme implemented. The performance of gMMC was tested in a sample problem of CBCT projection simulation for a homogeneous object. The results were compared to those obtained using gMCDRR, a GPU-based MC tool withmore » the conventional particle-by-particle simulation scheme. Results: Calculated scattered photon signals in gMMC agreed with those from gMCDRR with a relative difference of 3%. It took 3.1 hr. for gMCDRR to simulate 7.8e11 photons and 246.5 sec for gMMC to simulate 1.4e10 paths. Under this setting, both results attained the same ∼2% statistical uncertainty. Hence, a speed-up factor of ∼45.3 was achieved by this new path-by-path simulation scheme, where all the computations were spent on those photons contributing to the detector signal. Conclusion: We innovatively proposed a novel path-by-path simulation scheme that enabled a significant efficiency enhancement for MC particle transport simulations.« less

Authors:
 [1];  [2]; ; ;  [1];  [3]
  1. UT Southwestern Medical Center, Dallas, TX (United States)
  2. (China)
  3. Southern Medical University, Guangzhou (China)
Publication Date:
OSTI Identifier:
22545188
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 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; ALGORITHMS; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; MONTE CARLO METHOD; PARTICLE BEAMS; PERFORMANCE; PHOTON TRANSPORT; RADIOTHERAPY; SIMULATION; X-RAY SOURCES

Citation Formats

Xu, Y, Southern Medical University, Guangzhou, Tian, Z, Jiang, S, Jia, X, and Zhou, L. SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation. United States: N. p., 2015. Web. doi:10.1118/1.4924419.
Xu, Y, Southern Medical University, Guangzhou, Tian, Z, Jiang, S, Jia, X, & Zhou, L. SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation. United States. doi:10.1118/1.4924419.
Xu, Y, Southern Medical University, Guangzhou, Tian, Z, Jiang, S, Jia, X, and Zhou, L. Mon . "SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation". United States. doi:10.1118/1.4924419.
@article{osti_22545188,
title = {SU-E-T-58: A Novel Monte Carlo Photon Transport Simulation Scheme and Its Application in Cone Beam CT Projection Simulation},
author = {Xu, Y and Southern Medical University, Guangzhou and Tian, Z and Jiang, S and Jia, X and Zhou, L},
abstractNote = {Purpose: Monte Carlo (MC) simulation is an important tool to solve radiotherapy and medical imaging problems. Low computational efficiency hinders its wide applications. Conventionally, MC is performed in a particle-by -particle fashion. The lack of control on particle trajectory is a main cause of low efficiency in some applications. Take cone beam CT (CBCT) projection simulation as an example, significant amount of computations were wasted on transporting photons that do not reach the detector. To solve this problem, we propose an innovative MC simulation scheme with a path-by-path sampling method. Methods: Consider a photon path starting at the x-ray source. After going through a set of interactions, it ends at the detector. In the proposed scheme, we sampled an entire photon path each time. Metropolis-Hasting algorithm was employed to accept/reject a sampled path based on a calculated acceptance probability, in order to maintain correct relative probabilities among different paths, which are governed by photon transport physics. We developed a package gMMC on GPU with this new scheme implemented. The performance of gMMC was tested in a sample problem of CBCT projection simulation for a homogeneous object. The results were compared to those obtained using gMCDRR, a GPU-based MC tool with the conventional particle-by-particle simulation scheme. Results: Calculated scattered photon signals in gMMC agreed with those from gMCDRR with a relative difference of 3%. It took 3.1 hr. for gMCDRR to simulate 7.8e11 photons and 246.5 sec for gMMC to simulate 1.4e10 paths. Under this setting, both results attained the same ∼2% statistical uncertainty. Hence, a speed-up factor of ∼45.3 was achieved by this new path-by-path simulation scheme, where all the computations were spent on those photons contributing to the detector signal. Conclusion: We innovatively proposed a novel path-by-path simulation scheme that enabled a significant efficiency enhancement for MC particle transport simulations.},
doi = {10.1118/1.4924419},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}
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