PMID- 33263311
OWN - NLM
STAT- MEDLINE
DCOM- 20210120
LR  - 20220716
IS  - 1361-6560 (Electronic)
IS  - 0031-9155 (Print)
IS  - 0031-9155 (Linking)
VI  - 65
IP  - 23
DP  - 2020 Dec 2
TI  - GPU-accelerated Monte Carlo simulation of MV-CBCT.
PG  - 235042
LID - 10.1088/1361-6560/abaeba [doi]
AB  - Monte Carlo simulation (MCS) is one of the most accurate computation methods for 
      dose calculation and image formation in radiation therapy. However, the high 
      computational complexity and long execution time of MCS limits its broad use. In 
      this paper, we present a novel strategy to accelerate MCS using a graphic 
      processing unit (GPU), and we demonstrate the application in mega-voltage (MV) 
      cone-beam computed tomography (CBCT) simulation. A new framework that generates a 
      series of MV projections from a single simulation run is designed specifically 
      for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is 
      incorporated into the framework for the simulation of photon transport through a 
      phantom volume. The FastEPID method, which accelerates the simulation of MV 
      images, is modified and integrated into the framework. The proposed GPU-based 
      simulation strategy was tested for its accuracy and efficiency in a Catphan 604 
      phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, 
      and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great 
      simulation accuracy and excellent agreement with measurement and CPU-based 
      simulation in terms of reconstructed image qualities. The MV-CBCT simulation was 
      accelerated by factors of roughly 900-2300 using an NVIDIA Tesla V100 GPU card 
      against a 2.5 GHz AMD Opteron Processor 6380.
FAU - Shi, Mengying
AU  - Shi M
AD  - Medical Physics Program, Department of Physics and Applied Physics, University of 
      Massachusetts Lowell, Lowell, MA, United States of America. Brigham and Women's 
      Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, 
      United States of America.
FAU - Myronakis, Marios
AU  - Myronakis M
FAU - Jacobson, Matthew
AU  - Jacobson M
FAU - Ferguson, Dianne
AU  - Ferguson D
FAU - Williams, Christopher
AU  - Williams C
FAU - Lehmann, Mathias
AU  - Lehmann M
FAU - Baturin, Paul
AU  - Baturin P
FAU - Huber, Pascal
AU  - Huber P
FAU - Fueglistaller, Rony
AU  - Fueglistaller R
FAU - Lozano, Ingrid Valencia
AU  - Lozano IV
FAU - Harris, Thomas
AU  - Harris T
FAU - Morf, Daniel
AU  - Morf D
FAU - Berbeco, Ross I
AU  - Berbeco RI
LA  - eng
GR  - R01 CA188446/CA/NCI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20201202
PL  - England
TA  - Phys Med Biol
JT  - Physics in medicine and biology
JID - 0401220
SB  - IM
MH  - Computer Graphics
MH  - *Computer Simulation
MH  - *Cone-Beam Computed Tomography
MH  - *Monte Carlo Method
MH  - Phantoms, Imaging
MH  - Photons
PMC - PMC9100851
MID - NIHMS1804401
EDAT- 2020/12/03 06:00
MHDA- 2021/01/21 06:00
PMCR- 2022/05/13
CRDT- 2020/12/02 08:42
PHST- 2020/12/02 08:42 [entrez]
PHST- 2020/12/03 06:00 [pubmed]
PHST- 2021/01/21 06:00 [medline]
PHST- 2022/05/13 00:00 [pmc-release]
AID - 10.1088/1361-6560/abaeba [doi]
PST - epublish
SO  - Phys Med Biol. 2020 Dec 2;65(23):235042. doi: 10.1088/1361-6560/abaeba.