Comparison of depth-dose distributions of proton therapeutic beams calculated by means of logical detectors and ionization chamber modeled in Monte Carlo codes

• Influence of the bin structure on the proton dose distributions was examined for the MC simulations.
• The considered relative proton dose distributions in water correspond to the clinical application.
• MC simulations performed with the logical detectors and the ionization chamber model were compared.
• The advantage of the logical detector approach is that the calculation effectiveness is higher.

The success of proton therapy depends strongly on the precision of treatment planning. Dose distribution in biological tissue may be obtained from Monte Carlo simulations using various scientific codes making it possible to perform very accurate calculations. However, there are many factors affecting the accuracy of modeling. One of them is a structure of objects called bins registering a dose. In this work the influence of bin structure on the dose distributions was examined. The MCNPX code calculations of Bragg curve for the 60 MeV proton beam were done in two ways: using simple logical detectors being the volumes determined in water, and using a precise model of ionization chamber used in clinical dosimetry. The results of the simulations were verified experimentally in the water phantom with Marcus ionization chamber. The average local dose difference between the measured relative doses in the water phantom and those calculated by means of the logical detectors was 1.4% at first 25 mm, whereas in the full depth range this difference was 1.6% for the maximum uncertainty in the calculations less than 2.4% and for the maximum measuring error of 1%. In case of the relative doses calculated with the use of the ionization chamber model this average difference was somewhat greater, being 2.3% at depths up to 25 mm and 2.4% in the full range of depths for the maximum uncertainty in the calculations of 3%. In the dose calculations the ionization chamber model does not offer any additional advantages over the logical detectors. The results provided by both models are similar and in good agreement with the measurements, however, the logical detector approach is a more time-effective method.