Premium
Comparison of the Batho, ETAR and Monte Carlo dose calculation methods in CT based patient models
Author(s) -
du Plessis F. C. P.,
Willemse C. A.,
Lötter M. G.,
Goedhals L.
Publication year - 2001
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 - 10.1118/1.1357223
Subject(s) - monte carlo method , imaging phantom , nuclear medicine , dosimetry , radiation treatment planning , beam (structure) , materials science , physics , computational physics , mathematics , radiation therapy , optics , medicine , radiology , statistics
This paper shows the contribution that Monte Carlo methods make in regard to dose distribution calculations in CT based patient models and the role it plays as a gold standard to evaluate other dose calculation algorithms. The EGS4 based BEAM code was used to construct a generic 8 MV accelerator to obtain a series of x‐ray field sources. These were used in the EGS4 based DOSXYZ code to generate beam data in a mathematical water phantom to set up a beam model in a commercial treatment planning system (TPS), CADPLAN V.2.7.9. Dose distributions were calculated with the Batho and ETAR inhomogeneity correction algorithms in head/sinus, lung, and prostate patient models for 2 × 2 ,5 × 5 , and 10 × 10cm 2open x‐ray beams. Corresponding dose distributions were calculated with DOSXYZ that were used as a benchmark. The dose comparisons are expressed in terms of 2D isodose distributions, percentage depth dose data, and dose difference volume histograms (DDVH's). Results indicated that the Batho and ETAR methods contained inaccuracies of 20%–70% in the maxillary sinus region in the head model. Large lung inhomogeneities irradiated with small fields gave rise to absorbed dose deviations of 10%–20%. It is shown for a 10 × 10cm 2field that DOSXYZ models lateral scatter in lung that is not present in the Batho and ETAR methods. The ETAR and Batho methods are accurate within 3% in a prostate model. We showed how the performance of these inhomogeneity correction methods can be understood in realistic patient models using validated Monte Carlo codes such as BEAM and DOSXYZ.