Vol 19, No 6 (2014)
Original research articles
Published online: 2014-11-01

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Dosimetric effect of tissue heterogeneity for I prostate implants

Susana Maria Oliveira123, Nuno José Teixeira14, Lisete Fernandes456, Pedro Teles7, Pedro Vaz7
DOI: 10.1016/j.rpor.2014.03.004
Rep Pract Oncol Radiother 2014;19(6):392-398.

Abstract

Aim

To use Monte Carlo (MC) together with voxel phantoms to analyze the tissue heterogeneity effect in the dose distributions and equivalent uniform dose (EUD) for 125I prostate implants.

Background

Dose distribution calculations in low dose-rate brachytherapy are based on the dose deposition around a single source in a water phantom. This formalism does not take into account tissue heterogeneities, interseed attenuation, or finite patient dimensions effects. Tissue composition is especially important due to the photoelectric effect.

Materials and methods

The computed tomographies (CT) of two patients with prostate cancer were used to create voxel phantoms for the MC simulations. An elemental composition and density were assigned to each structure. Densities of the prostate, vesicles, rectum and bladder were determined through the CT electronic densities of 100 patients. The same simulations were performed considering the same phantom as pure water. Results were compared via dose–volume histograms and EUD for the prostate and rectum.

Results

The mean absorbed doses presented deviations of 3.3–4.0% for the prostate and of 2.3–4.9% for the rectum, when comparing calculations in water with calculations in the heterogeneous phantom. In the calculations in water, the prostate D90 was overestimated by 2.8–3.9% and the rectum D0.1cc resulted in dose differences of 6–8%. The EUD resulted in an overestimation of 3.5–3.7% for the prostate and of 7.7–8.3% for the rectum.

Conclusions

The deposited dose was consistently overestimated for the simulation in water. In order to increase the accuracy in the determination of dose distributions, especially around the rectum, the introduction of the model-based algorithms is recommended.

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