Characterization of tissue microstructure using ultrasonic backscatter: theory and technique for optimization using a Gaussian form factor.

Abstract

Characterization of tissue microstructure through ultrasonic backscatter is hypothesized to aid in detection and classification of diseased tissues. Radio frequency signals backscattered from tissues can be modeled according to the assumed shape, size, and distribution of scatterers in tissues. Power spectra of rf backscattered signals describe the frequency dependence of scatterers. Experimental measurements of ultrasonic backscatter from spontaneous mammary tumors in rats are obtained over the frequency range of 4 to 12 MHz. The power spectra measured from rat tumors are compared to theoretical power spectra derived from a 3D spatial autocorrelation function assuming a Gaussian distribution. Independent values of average scatterer diameter and acoustic concentration are obtained by approximating the measured power spectrum with a best-fit line. Enhanced B-mode images are made of the rat tumors and surrounding tissues with superimposed regions of interest quantified by estimated average scatterer sizes and acoustic concentrations. Scattering properties estimated inside the tumors and in surrounding tissues are shown to be distinct. Overall, estimates showed a 44.8% increase of average scatterer diameter inside the tumor as compared to tissues outside the tumor. With the exception of one rat, all estimates of the scatterers' average acoustic concentration inside the tumor were less than outside the tumors.