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1.
Med Phys ; 33(4): 1041-52, 2006 Apr.
Article in English | MEDLINE | ID: mdl-16696481

ABSTRACT

Although conventional mammography is currently the best modality to detect early breast cancer, it is limited in that the recorded image represents the superposition of a three-dimensional (3D) object onto a 2D plane. Recently, two promising approaches for 3D volumetric breast imaging have been proposed, breast tomosynthesis (BT) and CT breast imaging (CTBI). To investigate possible improvements in lesion detection accuracy with either breast tomosynthesis or CT breast imaging as compared to digital mammography (DM), a computer simulation study was conducted using simulated lesions embedded into a structured 3D breast model. The computer simulation realistically modeled x-ray transport through a breast model, as well as the signal and noise propagation through a CsI based flat-panel imager. Polyenergetic x-ray spectra of Mo/Mo 28 kVp for digital mammography, Mo/Rh 28 kVp for BT, and W/Ce 50 kVp for CTBI were modeled. For the CTBI simulation, the intensity of the x-ray spectra for each projection view was determined so as to provide a total average glandular dose of 4 mGy, which is approximately equivalent to that given in conventional two-view screening mammography. The same total dose was modeled for both the DM and BT simulations. Irregular lesions were simulated by using a stochastic growth algorithm providing lesions with an effective diameter of 5 mm. Breast tissue was simulated by generating an ensemble of backgrounds with a power law spectrum, with the composition of 50% fibroglandular and 50% adipose tissue. To evaluate lesion detection accuracy, a receiver operating characteristic (ROC) study was performed with five observers reading an ensemble of images for each case. The average area under the ROC curves (Az) was 0.76 for DM, 0.93 for BT, and 0.94 for CTBI. Results indicated that for the same dose, a 5 mm lesion embedded in a structured breast phantom was detected by the two volumetric breast imaging systems, BT and CTBI, with statistically significant higher confidence than with planar digital mammography, while the difference in lesion detection between BT and CTBI was not statistically significant.


Subject(s)
Breast Neoplasms/diagnostic imaging , Imaging, Three-Dimensional/methods , Mammography/methods , Models, Biological , Radiographic Image Enhancement/methods , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, Spiral Computed/methods , Algorithms , Computer Simulation , Humans , Information Storage and Retrieval/methods , Observer Variation , Reproducibility of Results , Sensitivity and Specificity , Tomography/methods
2.
Phys Med Biol ; 49(11): 2183-95, 2004 Jun 07.
Article in English | MEDLINE | ID: mdl-15248571

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.


Subject(s)
Algorithms , Breast Diseases/diagnostic imaging , Calcinosis/diagnostic imaging , Imaging, Three-Dimensional/methods , Mammography/methods , Radiographic Image Enhancement/methods , Radiographic Image Interpretation, Computer-Assisted/methods , Computer Simulation , Equipment Failure Analysis/methods , Image Enhancement/methods , Imaging, Three-Dimensional/instrumentation , Mammography/instrumentation , Models, Biological , Pattern Recognition, Automated/methods , Radiographic Image Enhancement/instrumentation , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Tomography, X-Ray Computed/instrumentation , Tomography, X-Ray Computed/methods
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