title: Contrast-to-noise ratio in magnification mammography: a Monte Carlo study.
abstract: Magnification views are a common way to perform a secondary examination when suspicious abnormalities are found in a screening mammogram. The visibility of microcalcifications and breast lesions is restricted by the compromise between the image quality and the absorbed dose. In this study, image quality characteristics in magnification mammography were evaluated based on Monte Carlo techniques. A breast phantom was utilized, simulating a homogeneous mixture of adipose and glandular tissue in various percentages of glandularity, containing inhomogeneities of various sizes and compositions. The effect of the magnification degree, breast glandularity, tube voltage and anode/filter material combination on image quality characteristics was investigated in terms of a contrast-to-noise ratio (CNR). A performance index PI(nu) was introduced in order to study the overall performance of various anode/filter combinations under different exposure parameters. Results demonstrate that CNR is improved with the degree of magnification and degraded as the breast glandularity is increased. Degree of magnification 1.3 offers the best overall performance for most of the anode/filter combinations utilized. Under magnification conditions, the role of dose is demoted against the image quality, as magnification views are secondary, diagnostic examinations and not screening procedures oriented to non-symptomatic women. For decreased image quality weighting, some anode/filter combinations different from Mo/0.030 mmMo can be utilized as they offer a similar performance index. However, if the desired weighting for the image quality is high, the Mo/0.030 mmMo combination has the best overall performance.
authors.affiliation: Department of Medical Physics, University of Patras, School of Medicine, 265 00 Patras, Greece.
authors.forename: M
authors.initials: M
authors.lastname: Koutalonis
authors.forename: H
authors.initials: H
authors.lastname: Delis
authors.forename: G
authors.initials: G
authors.lastname: Spyrou
authors.forename: L
authors.initials: L
authors.lastname: Costaridou
authors.forename: G
authors.initials: G
authors.lastname: Tzanakos
authors.forename: G
authors.initials: G
authors.lastname: Panayiotakis
mesh_terms: D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008327:Mammography / Q000295:instrumentation* / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D014963:X-Ray Intensifying Screens