A Monte Carlo tutorial and the application for radiotherapy treatment planning.
Monte Carlo-based treatment planning algorithms are advancing rapidly and will certainly be implemented as part of conventional treatment planning systems in the near future. This paper was designed as a basic tutorial for using the Monte Carlo method as applied to radiotherapy treatment planning. The tutorial addresses the basic transport differences between photon and electron transport as well as the sampling distributions. The implementation of a virtual linac source model and the conversion from the Monte Carlo source modeling reference plane into the treatment reference plane is discussed. The implementation of a thresholding algorithm for converting CT electron density to patient specific materials is also presented. A 6-field prostate boost treatment is used to compare a conventional treatment planning algorithm (pencil beam model) with a Monte Carlo simulation algorithm. The agreement between the 2 calculation methods is good based upon the qualitative comparison of the isodose distribution and the dose-volume histograms for the prostate and the rectum. The effects of statistical uncertainty on the Monte Carlo calculation are also presented.
Demarco
J J
JJ
UCLA Department of Radiation Oncology, University of California Los Angeles, 90095-6951, USA. demarco@radonc.ucla.edu
Chetty
I J
IJ
Solberg
T D
TD
D006801:Humans; D009010:Monte Carlo Method; D009369:Neoplasms / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted