Detection of lesions in mammographic structure

This paper is a report on very surprising results from recent work on detection of real lesions in digitized mammograms. The experiments were done using a novel experimental procedure with hybrid images. The lesions (signals) were real tumor masses extracted from breast tissue specimen radiographs. In the detection experiments, the tumors were added to digitized normal mammographic backgrounds. The results of this new work have been both novel and very surprising. Contrast thresholds increased with increasing lesion size for lesions larger than approximately 1 mm in diameter. Earlier work with white noise, radiographic image noise, computed tomography (CT) noise and some types of patient structure have accustomed us to a particular relationship between lesion size and contrast for constant detectability. All previous contrast/detail (CD) diagrams have been similar, the contrast threshold decreases as lesion size increases and flattens at large lesion sizes. The CD diagram for lesion detection in mammographic structure is completely different. It will be shown that this is a consequence of the power-law dependence of the projected breast tissue structure spectral density on spatial frequency. Mammographic tissue structure power spectra have the form P(f) equals B/f(beta ), with an average exponent of approximately 3 (range from 2 to 4), and are approximately isotropic (small angular dependence). Results for two-alternative forced-choice (2AFC) signal detection experiments using 4 tumor lesions and one mathematically generated signal will be presented. These results are for an unbiased selection of mammographic backgrounds. It is possible that an additional understanding of the effects of breast structure on lesion detectability can be obtained by investigating detectability in various classes of mammographic backgrounds. This will be the subject of future research.