# Nuclear Science and Techniques

《核技术》(英文版) ISSN 1001-8042 CN 31-1559/TL     2019 Impact factor 1.556

Nuclear Science and Techniques ›› 2015, Vol. 26 ›› Issue (3): 030303

### Computation and parameterization of normalized glandular dose using Geant4

Omrane Kadri,1, 2 Mohammed Ali Alnafea,1 and Khaled Shamma1

1. 1Department of Radiological Sciences, College of Applied Medical Sciences, King Saud University, PO Box 10219, Riyadh 11433, Saudi Arabia
2National Center for Nuclear Sciences and Technologies, 2020 Tunis, Tunisia
• Supported by:

Supported by the National Plan for Science, Technology and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia (No. 1827)

Omrane Kadri, Mohammed Ali Alnafea, and Khaled Shamma. Computation and parameterization of normalized glandular dose using Geant4.Nuclear Science and Techniques, 2015, 26(3): 030303

Abstract:

The average absorbed dose in glandular tissue is the most appropriate parameter for the assessment of the radiation-induced risk during breast imaging. The aims of this work concern: (1) the investigation of the variation effect of any related update to photon cross-section data-bases on the computation of the normalized glandular dose (DgN) for mammography quality control tests and (2) the proposition of a parameterization method leading to provide DgN values function of the breast thickness (T) and the particle energy (E) instead of E alone, as normally known. We analyzed the change effect of the photon cross-section data-bases on the computation of DgN. Those coefficients, generated using the Geant4 Monte Carlo toolkit, were studied over a range of compressed breast thickness of 2–8 cm for monoenergetic (1–120 keV by 1 keV intervals) and polyenergetic (23–35 kVp by 2 kVp intervals) X-ray beams. Moreover, breast tissue composition ranging from about 0% glandular (about 100% adipose) to 100% glandular (0% adipose) was also covered. The successful parameterization of DgN look-up table function of the breast thickness and energy, will compact its analytical form without loss of accuracy. All parameterization fits resulted in r2 values of 0.999 or better.