title: Normalized glandular dose (DgN) coefficients for flat-panel CT breast imaging.
abstract: The development of new digital mammography techniques such as dual-energy imaging, tomosynthesis and CT breast imaging will require investigation of optimal camera design parameters and optimal imaging acquisition parameters. In optimizing these acquisition protocols and imaging systems it is important to have knowledge of the radiation dose to the breast. This study presents a methodology for estimating the normalized glandular dose to the uncompressed breast using the geometry proposed for flat-panel CT breast imaging. The simulation uses the GEANT 3 Monte Carlo code to model x-ray transport and absorption within the breast phantom. The Monte Carlo software was validated for breast dosimetry by comparing results of the normalized glandular dose (DgN) values of the compressed breast to those reported in the literature. The normalized glandular dose was then estimated for a range of breast diameters from 10 cm to 18 cm using an uncompressed breast model with a homogeneous composition of adipose and glandular tissue, and for monoenergetic x-rays from 10 keV to 120 keV. These data were fit providing expressions for the normalized glandular dose. Using these expressions for the DgN coefficients and input variables such as the diameter, height and composition of the breast phantom, the mean glandular dose for any spectra can be estimated. A computer program to provide normalized glandular dose values has been made available online. In addition, figures displaying energy deposition maps are presented to better understand the spatial distribution of dose in CT breast imaging.
authors.affiliation: Department of Radiology, University of Massachusetts, Medical School, Worcester, MA 01655, USA.
authors.forename: Samta C
authors.initials: SC
authors.lastname: Thacker
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Glick
mesh_terms: D001822:Body Burden; D001940:Breast / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D018499:Linear Energy Transfer / Q000502:physiology; D008327:Mammography / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D009928:Organ Specificity; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement / Q000379:methods*; D011874:Radiometry / Q000379:methods*; D012062:Relative Biological Effectiveness; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors