Breast cancer is the leading cause of cancer deaths in female subjects. Screening Digital Mammography (DM) is the principal technique used to detect tumors even in an early stage, allowing greater possibilities for treatments. Since DM is performed using ionizing radiation, Mean Glandular Dose (MGD in the US dosimetry protocols, or Average Glandular Dose AGD in the Europeans protocols) is adopted for cancer risk estimates and it must be assessed with an accurate dosimetry. Dose to the gland can't be measured directly and Monte Carlo (MC) simulations are performed to evaluate MGD, multiplying incident air kerma by suitable conversion factors computed by MC codes. An evolution of DM is represented by Digital Breast Tomosynthesis (DBT), widespread in clinic in the last years, which allows to overcome the overlapping tissues of the (2D) DM to obtain a more realistic reconstruction of the breast anatomy. For dosimetry purposes in both DM and DBT, until now, as geometric assumption, the compressed breast has been considered with a simple geometry, using a homogeneous compound of adipose and glandular tissues surrounded by 5 mm thick adipose skin. Research groups focus their efforts to introduce heterogeneous breast models which better can represent the breast anatomy to be included in their MC simulations by means of voxelized phantoms that replace the continuous geometric representation of the breast into a set of voxels. Moreover, in the last years, thanks to the spread of 3D printers, the state of the art is the production of built-in-house phantoms presenting attenuation characteristics and/or digital images similar to those of the real compressed breasts. In this paper we will discuss Monte Carlo methods needed for the estimation of the mean glandular dose in both DM and DBT. We will consider various breast anatomies, investigating the influence of different breast size, composition and skin thickness. Furthermore, a discussion about low density 3D printing materials for physical breast phantoms will be included.
Monte Carlo methods to evaluate the mean glandular dose in mammography and digital breast tomosynthesis
Tucciariello R. M.Primo
;Barca P.;Lamastra R.;Fantacci M. E.Ultimo
2020-01-01
Abstract
Breast cancer is the leading cause of cancer deaths in female subjects. Screening Digital Mammography (DM) is the principal technique used to detect tumors even in an early stage, allowing greater possibilities for treatments. Since DM is performed using ionizing radiation, Mean Glandular Dose (MGD in the US dosimetry protocols, or Average Glandular Dose AGD in the Europeans protocols) is adopted for cancer risk estimates and it must be assessed with an accurate dosimetry. Dose to the gland can't be measured directly and Monte Carlo (MC) simulations are performed to evaluate MGD, multiplying incident air kerma by suitable conversion factors computed by MC codes. An evolution of DM is represented by Digital Breast Tomosynthesis (DBT), widespread in clinic in the last years, which allows to overcome the overlapping tissues of the (2D) DM to obtain a more realistic reconstruction of the breast anatomy. For dosimetry purposes in both DM and DBT, until now, as geometric assumption, the compressed breast has been considered with a simple geometry, using a homogeneous compound of adipose and glandular tissues surrounded by 5 mm thick adipose skin. Research groups focus their efforts to introduce heterogeneous breast models which better can represent the breast anatomy to be included in their MC simulations by means of voxelized phantoms that replace the continuous geometric representation of the breast into a set of voxels. Moreover, in the last years, thanks to the spread of 3D printers, the state of the art is the production of built-in-house phantoms presenting attenuation characteristics and/or digital images similar to those of the real compressed breasts. In this paper we will discuss Monte Carlo methods needed for the estimation of the mean glandular dose in both DM and DBT. We will consider various breast anatomies, investigating the influence of different breast size, composition and skin thickness. Furthermore, a discussion about low density 3D printing materials for physical breast phantoms will be included.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
