A REVIEW OF MONTE CARLO METHODS AND THEIR APPLICATION IN MEDICAL PHYSICS FOR SIMULATING RADIATION TRANSPORT
Keywords:
Keywords: Monte Carlo, medical physics, radiation transport, EGSnrc, simulation, dose, random numbersAbstract
Monte Carlo methods are used to calculate statistical behavior through the use
of random number generators and probability density functions. They have been used
extensively in medical physics for research in radiotherapy, designing technology,
dosimetry, and advanced clinical applications. This paper provides a background on
Monte Carlo methods and a review of radiation therapy physics and dosimetry.
Additionally, there is a discussion of the different ways Monte Carlo methods are used
in medical physics as well as a review of current research related to Monte Carlo
methods. The final portion of this paper contains my own Monte Carlo simulation using
the EGSnrc software toolkit to carry out two different simulations. One simulation
serves as a basic introduction to using the software and demonstrates some of its
capabilities, while the other is a more complex simulation that models a realistic
scenario in medical physics.
References
References
Rogers, D.W.O., Faddegon, B.A., Ding, G.X., & Ma, C.M. (1995). BEAM: A Monte
Carlo code to simulate radiotherapy treatment units. Medical Physics, 22(5), 503-
Kawrakow, I., & Walters, B.R.B. (2006). Efficient photon beam dose calculations
using DOSXYZnrc with BEAMnrc. Medical Physics, 33(8), 3046-3056.
Salvat, F., Fernández-Varea, J.M., & Sempau, J. (2010). PENELOPE-2008: A code
system for Monte Carlo simulation of electron and photon transport. OECD Nuclear
Energy Agency.
Sechopoulos, I., & Rogers, D.W.O. (2011). Monte Carlo simulation in medical
imaging. Medical Physics, 38(9), 5025-5043.
Paganetti, H. (2018). Range uncertainties in proton therapy and the role of Monte
Carlo simulations. Physics in Medicine & Biology, 63(5), 05TR01.
Hsieh J: Computed tomography: Principles, design, artifacts, and recent advances.
SPIE, Bellingham, WA. (2003).
Fleischmann D, Boas FE, Tye GA, Sheahan D, Molvin LZ: Effect of low radiation
dose on image noise and subjective image quality for analytic vs iterative image
reconstruction in abdominal CT. In: RSNA. Chicago 2011.
Vandenberghe S, D'Asseler Y, Van de Walle R et al.: Iterative reconstruction
algorithms in nuclear medicine. Computerized Medical Imaging and Graphics 25(2),
-111 (2001).
Fleischmann D, Boas FE: Computed tomography--old ideas and new technology.
Eur Radiol 21(3), 510-517 (2011).
Yu Z, Thibault JB, Bouman CA, Sauer KD, Hsieh J: Fast model-based X-ray CT
reconstruction using spatially nonhomogeneous ICD optimization. IEEE Trans
Image Process 20(1), 161-175 (2011).
Agostinelli, S., et al. (2003). "GEANT4—a simulation toolkit." Nuclear Instruments
and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors
and Associated Equipment, 506(3), 250-303.
Sempau, J., et al. (2003). "Experimental benchmarks of the Monte Carlo code
PENELOPE." Nuclear Instruments and Methods in Physics Research Section B:
Beam Interactions with Materials and Atoms, 207(2), 107-123.
