Abstract

Introduction Recently, cancer treatment improvement enabled an increase in patients’ survival rate. In more than half of the cases, radiotherapy participates in the cure for cancer. The efficacy of this technique is well known but it inevitably delivers doses to normal tissues exposing them to radio-induced complications risks [1] . Moreover, the longer patients’ life expectancy increases the risk of developing long-term complications such as second cancers. Thus, evaluating the risks following cancer treatment involving radiotherapy constitutes a major challenge. In this context, an experimental tool has been developed to evaluate normal tissue doses delivered by the different radiotherapy techniques. Those dosimetric data are prerequisites for risk evaluation. Methods The tool developed on Matlab is based on 3D dose reconstruction from 2D dose measurements performed using radiochromic films placed between phantom slices. The tool proceeds to fine spatial films/TPS dose matching near the target volume and then reconstructs the 3D dose distribution by interpolation of films dose measurements. Finally, interesting dosimetric data such as dose-volume histograms are evaluated. A first validation of the tool has been performed with the EasyCube phantom irradiated with two films spaced 2 cm apart and placed in target volume. After scanning and contouring, the phantom was irradiated according to a treatment planning with the films in place. Films were analyzed using a rigorous protocol [2] developed by our group. Results Both 2D and volumetric comparisons between measured and planned doses gave good results. Indeed, 89.2% of points pass the 3 mm/3% gamma test when comparing interpolated dose distribution and planned dose on the middle slice. Likewise, a 2.6% discrepancy on mean PTV doses has been observed between the two distributions and the mean shift between the 0.4 Gy isodoses is of 0.10 mm on the middle slice. Conclusions The original tool developed in this work enables an experimental evaluation of normal tissue doses: essential dosimetric data for risk evaluation models. The preliminary feasibility study shows promising results. Validation and optimization on a more important volume is currently ongoing. Finally, validation using 3D gel dosimetry is considered.

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