Abstract ID: 60 Monte Carlo simulation and experimental validation of glandular dose coefficients in digital breast tomosynthesis

• Published in: Physica medica 2017-10, Vol.42, p.11-12
• Main Authors: Mettivier, G., Lillo, F. Di, Sarno, A., Bliznakova, K., Bliznakov, Z, Bosmans, H., Russo, P.
• Format: Article
• Language: English
• ISSN: 1120-1797; 1724-191X
• DOI: 10.1016/j.ejmp.2017.09.029

The mean radiation dose to the glandular tissue and its dependence on the irradiation geometry, beam quality, breast size and composition in digital breast tomosynthesis (DBT) exams have been studied extensively via Monte Carlo calculations [1]. On the other hand, there are few comprehensive studies on the dose distribution within the irradiated breast [2]. The distribution of glandular dose for breast irradiation from a plurality of angles, as occurs in DBT, may be of large interest in scanner optimization as well as for developing suitable models for the evaluation of the cancer risk related to the X-ray exposure for non–homogeneous irradiation. For this reason, it is of interest to evaluate the level of homogeneity of the dose spread, via the assessment of 3D dose maps in breast models during a DBT scan. This work aimed at evaluating, via Monte Carlo (MC) simulations and measurements using radiochromic films, the dose distribution within compressed layered breast phantoms during DBT scans. For this purpose, two phantoms were employed: a PMMA homogeneous phantom and a heterogeneous phantom simulating a 50% glandular breast. A series of pre-calibrated (vs free-in-air air kerma) film pieces were inserted between the phantom slices and the 3D dose maps were measured for a set of DBT scans on different commercial units, for different sample thicknesses, at various exposure technique factors. We developed an MC code based on GEANT4 toolkit ver. 10.00, simulating the clinical setup specifications, whose results have been compared to measurements. This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 692097 for the MaXIMA project: Three dimensional breast cancer models for X-ray imaging research.