Calculation of dose decrease in a finite phantom of a 192Ir point source
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Updated: Jul 10, 2026

Irradiator Commissioning and Dosimetry for Assessment of LQ α and β Parameters, Radiation Dosing Schema, and in vivo Dose Deposition
Published on: March 11, 2021
Corinna Melchert1, P Kohr, R Schmidt
1Department of Radiotherapy, University of Luebeck, Ratzeburger Allee 160, Luebeck, Schleswig-Holstein 23538, Germany. corinna.melchert@uk-sh.de
Abstract:
The purpose of this study was to calculate the dose decrease in a finite phantom of a 192Ir-point source by using a new algorithm based on field theory. The methods used included the phenomenological application of the principle "mirror image of an electric point source in front of a dielectric semi-plateau" to a radioactive source in a finite phantom results in a function to calculate the dose decrease near the surface. Measurements were done in a water phantom in three different experimental setups. To verify the calculated results Monte Carlo (MC) simulations of dose distribution of a 192Ir point source in 34 x 40 x 40 cm3 water were carried out. The strength of mirror source was found -0.103 of the real source. A lack scatter function was necessary to handle the dose decrease very close to surface. The measured and calculated dose values differed less than 0.9%. Both MC simulations and the new algorithm show the dose decrease near phantom surface with differences less than 2% between each other. The new algorithm based on field theory calculated the dose decrease of a 192Ir point source in a finite phantom with a very good agreement to measured and simulated data. A clinical example, which affects only a single planar boundary, is given by using molds in the treatment of skin tumors. This was calculated with the new algorithm presented in this article. The comparison with the common algorithm demonstrates the differences that might cause an overestimation of the dose, which probably leads an underdosing of the tumor. The general use of the new algorithm in brachytherapy where a variety of boundary shapes are encountered has to be verified seriously.
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