Paper
22 May 2020 Monte Carlo dose evaluation of different fibroglandular tissue distribution in breast imaging
Author Affiliations +
Proceedings Volume 11513, 15th International Workshop on Breast Imaging (IWBI2020); 115130G (2020) https://doi.org/10.1117/12.2564278
Event: Fifteenth International Workshop on Breast Imaging, 2020, Leuven, Belgium
Abstract
This work compares estimates of the radiation dose in mammography obtained using three different fibroglandular tissue distributions. Ninety volumetric images of patient breasts were acquired with a dedicated breast CT system and the voxels automatically classified as containing skin, adipose, or glandular tissue. The classified images underwent simulated mechanical compression to mimic the mammographic cranio-caudal acquisition. The voxels containing fibroglandular and adipose tissue were then distributed in the breast phantoms following three different methods: patient-based (i.e., maintaining the original distribution), homogeneous (i.e., each voxel is a homogeneous mixture of adipose and glandular tissue) and newly-proposed continuous (i.e., the glandular tissue is distributed according to a general model, derived from the patient breast CT data). All breast phantoms were used in Monte Carlo simulations to estimate the radiation dose. The results show that the doses estimated using the continuous fibroglandular tissue distribution agree within 3% of the doses estimated using the heterogeneous patient-based distribution, and that it leads to a dose reduction of 27% compared to the homogeneous distribution.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. M. Arana Peña, C. Fedon, E. García, O. Diaz, R. Longo, D. R. Dance, and I. Sechopoulos "Monte Carlo dose evaluation of different fibroglandular tissue distribution in breast imaging", Proc. SPIE 11513, 15th International Workshop on Breast Imaging (IWBI2020), 115130G (22 May 2020); https://doi.org/10.1117/12.2564278
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Cited by 3 scholarly publications.
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KEYWORDS
Breast

Tissues

Monte Carlo methods

Image compression

Mammography

X-rays

Breast imaging

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