title: Microcalcification detection using cone-beam CT mammography with a flat-panel imager.
abstract: The purpose of this study was to investigate microcalcification detectability using CT mammography with a flat-panel imager. To achieve this, a computer simulation was developed to model an amorphous-silicon, CsI based flat-panel imager system using a linear cascaded model. The breast was modelled as a hemi-ellipsoid shape with composition of 50% adipose and 50% glandular tissue. Microcalcifications were modelled as small spheres having a composition of calcium carbonate. The results show that with a mean glandular dose equivalent to that typically used in two-view screening mammography, CT mammography with a flat-panel detector is capable of providing images where most microcalcifications are detectable. A receiver operating characteristic (ROC) study was conducted by five physicist observers viewing simulated CT mammography reconstructions. The results suggest that the microcalcification with its diameter equal to or greater than 0.175 mm can be detected with an average area under the ROC curve (AUC) greater than 0.95 using 0.1 or 0.2 mm pixelized detectors. The results also indicate that the optimal pixel size of the detector is around 0.2 mm for microcalcification detection, based on the trade-off between detectability of microcalcifications and the time required for data acquisition and reconstruction.
authors.affiliation: Department of Radiology, University of Massachusetts, Medical School, Worcester, MA 01655, USA. xing.gong@umassmed.edu
authors.forename: Xing
authors.initials: X
authors.lastname: Gong
authors.forename: Aruna A
authors.initials: AA
authors.lastname: Vedula
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Glick
mesh_terms: D000465:Algorithms; D001941:Breast Diseases / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D019544:Equipment Failure Analysis / Q000379:methods; D007089:Image Enhancement / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000295:instrumentation / Q000379:methods*; D008327:Mammography / Q000295:instrumentation / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000295:instrumentation / Q000379:methods