Abstract : ABSTRACT
Screening mammography claimed to be associated with an increased risk of breast cancer. To justify screening, only a small increase in diagnostic performance can contribute to the preservation of an overwhelming number of women. Thus, optimal image quality must be taken into account on screening program. Breast density correlated with the accuracy of X-ray mammography and used as an indicator to convey information about the difficulty of tumour detections. The risk-benefit investigation should, focus on the performance of the examination. A well-known simulator, the modern Geant4 code, was used to model all the X-ray tube components of a molybdenum ( ) target / filter ( / ). In addition, heterogeneous breast phantoms with thickness of 4 cm and different ranges of glandular tissues starting from 5% glandularity up to 100% simulated. At first all, the simulations validated by obtaining the energy spectra of molybdenum , with a thickness of 50μm in the interval between 10 to 28 keV. In all cases, a tumour of 5 mm in diameter implanted within prevalence regions of glandular tissue. All obtained data evaluated to find a relationship between small-size tumour detection at different concentration of glandular tissue as well as the possible improvement of mammography image quality. The system performance assessed in terms of the Contrast-to-Noise Ratio (CNR) in multiple regions within the breast phantom. Results, suggest higher CNR values at lower mammary gland tissue ratio. Breast model was low with concentration >50%. Particularly, in position 1 the value was 0.026 but 0.26 at position 2. A high concentration at <50% (position 1=0.051 and position 2=0.348). CNR confirmed a strong negative association with all different mammary gland density concentrations. CNR predicted and used for measuring the diagnostic reliability of mammography tumour detection. Results suggested that the concentration of the glandular tissue i.e. breast density is the appropriate measure to describe the risks to which the radiation is exposed. In this case, an accurate estimate of the glandular tissue fraction must be known.
Keywords: Mammography Tube Modelling; X-ray spectra; Breast Cancer; Geant4; Glandular Fraction; Breast Density
Keyword : Mammography Tube Modelling; X-ray spectra; Breast Cancer; Geant4; Glandular Fraction; Breast Density