title: Quantification of breast density with dual energy mammography: a simulation study.
abstract: Breast density, the percentage of glandular breast tissue, has been identified as an important yet underutilized risk factor in the development of breast cancer. A quantitative method to measure breast density with dual energy imaging was investigated using a computer simulation model. Two configurations to measure breast density were evaluated: the usage of monoenergetic beams and an ideal detector, and the usage of polyenergetic beams with spectra from a tungsten anode x-ray tube with a detector modeled after a digital mammography system. The simulation model calculated the mean glandular dose necessary to quantify the variability of breast density to within 1/3%. The breast was modeled as a semicircle 10 cm in radius with equal homogenous thicknesses of adipose and glandular tissues. Breast thicknesses were considered in the range of 2-10 cm and energies in the range of 10-150 keV for the two monoenergetic beams, and 20-150 kVp for spectra with a tungsten anode x-ray tube. For a 4.2 cm breast thickness, the required mean glandular doses were 0.183 microGy for two monoenergetic beams at 19 and 71 keV, and 9.85 microGy for two polyenergetic spectra from a tungsten anode at 32 and 96 kVp with beam filtrations of 50 microm Rh and 300 microm Cu for the low and high energy beams, respectively. The results suggest that for either configuration, breast density can be precisely measured with dual energy imaging requiring only a small amount of additional dose to the breast. The possibility of using a standard screening mammogram as the low energy image is also discussed.
authors.affiliation: Department of Radiological Sciences, University of California, Irvine, California 92697, USA.
authors.forename: Justin L
authors.initials: JL
authors.lastname: Ducote
authors.forename: Sabee
authors.initials: S
authors.lastname: Molloi
mesh_terms: D000273:Adipose Tissue / Q000378:metabolism; D000465:Algorithms; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D055088:Early Detection of Cancer; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D015233:Models, Statistical; D009010:Monte Carlo Method; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012984:Software; D014414:Tungsten / Q000737:chemistry; D014965:X-Rays
chemical_list: D014414:Tungsten