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SU‐FF‐T‐288: Initial Experience with a Commercial Monte Carlo Electron Treatment Planning System
Author(s) -
Mah D,
Hong L,
Yaparpalvi R,
Engler M
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2241205
Subject(s) - monte carlo method , electron , ionization chamber , physics , dosimeter , computational physics , dosimetry , cathode ray , optics , nuclear medicine , ionization , materials science , mathematics , statistics , nuclear physics , medicine , radiation , ion , quantum mechanics
Introduction: Monte Carlo modeling of clinical electron beams has the potential to substantially improve accuracy and quality of treatment planning, as excessive compute time and lack of commercial availability has hindered its application. Here we present a preliminary evaluation of a commercial electron Monte Carlo algorithm. Methods and Materials: Percent depth dose and profiles of 6‐20 MeV electrons and 6×6 – 25×25 cm cones were measured in a water tank at 100 cm SSD using a Farmer chamber for electrons. Absolute output was measured at 110 and 100 cm SSDs. Outputs and distributions of two extreme test cases were measured: a 2.1 cm × 3 cm insert in a 6×6 cone and a 2.8 cm × 15.7 cm long slit on a 25×25 cone. The algorithm's ability to accurately model relative and absolute dose of an obliquely (30°) oriented beam was evaluated ionization chamber measurements. Clinical cases with were checked using Mosfet dosimeters in vivo . Monte Carlo calculations were performed with a 2 mm grid, and smoothing filters provided with the algorithm were applied to minimize noise in the data. Results: Agreement of 2% of measured and modeled doses was found over the evaluated range of energies, cones, obliquities and SSDs. Compute times of 1–5 minutes were a function of increasing field size. Visual comparison of the shapes of the profiles was in agreement with measurement. Profiles of the eccentric geometry test cases appeared to be to be physically unrealistic (e.g. an inverted V) in the smaller dimension suggesting that the beam model was not valid. Conclusions: The Monte Carlo electron algorithm provides accurate distributions for most clinical cases. For extreme cases, measurements should be made to test the accuracy of the system, and further development of the algorithm is recommended.