Computer-aided tissue characterization using ultrasound-induced thermal effects: analytical formulation and in-vitro animal study

Abstract

Ultrasound radio-frequency (RF) time series analysis provides an effective tissue characterization method to differentiate between healthy and cancerous prostate tissues. In this paper, an analytical model is presented that partially describes the variations in tissue acoustic properties that accompany ultrasound RF time series acquisition procedures. These ultrasound-induced effects, which depend on tissue mechanical and thermophysical properties, are hypothesized to be among the major contributors to the tissue typing capabilities of the RF time series analysis. The model is used to derive two tissue characterization features. The two features are used with a support vector machine classifier to characterize three animal tissue types: chicken breast, bovine liver, and bovine steak. Accuracy values as high as 90% are achieved when the proposed features are employed to differentiate these tissue types. The proposed model may provide a framework to optimize the ultrasound RF time series analysis for future clinical procedures.