Ultrasonic quantification of the tissue microstructure of spontaneous mammary tumors in rats

The quantification of tissue microstructure using ultrasound can aid in the detection and classification of disease. Eight retired breeder were acquired that had developed spontaneous mammary tumors. Two-dimensional B-mode images of the rat tumors were constructed from backscattered echoes. After scanning, tumors were dissected free from each rat, trimmed in the plane of ultrasound exposure, fixed in 10 % neutral-buffered formalin, embedded in paraffin, sectioned at 5 /spl mu/m, and stained with hematoxylin and eosin. Tumors were diagnosed microscopically as mammary gland fibroadenomas. Regions-of-interest (ROIs) were selected in the tumors and surrounding tissues and scatterer properties (average scatterer size and acoustic concentration) were estimated from the backscattered RF signal. Scatterer estimates were made by using least squares to fit a line to the measured form factor that was calculated from the backscattered power spectrum. Noise reduces the ability to make estimates of scatterer properties. A weighting scheme was used to reduce the effects of noise and increase the ability to make accurate estimates. Comparison of scatterer estimates made between normal tissues and tissues inside the tumors were made. On average, the estimated scatterer diameters inside the tumors were 30 % larger at 107 micrometers than estimates of scatterer diameters outside the tumors averaging 82 micrometers. Similarly, the average acoustic concentration estimated inside the tumor was 3.16/spl times/10/sup -2/ mm/sup -3/ as opposed to 0.746 mm/sup -3/ for outside the tumor. In all but one of the rats, there was a statistically significant difference (P<0.05) between estimates of scatterer properties made inside the tumors and in surrounding healthy tissues. Enhanced B-mode images were constructed by superimposing colored pixels that corresponding to the estimated scatterer properties on the gray-scale B-mode images. The enhanced B-mode images also showed differences between tissues inside and outside the tumors.