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.

Ultrasound-Guided Characterization of Interstitial Ablated Tissue Using RF Time Series: Feasibility Study

“…It should be noted that the characterization capabilities of RF time series have been successfully demonstrated elsewhere with different users, transducers and systems, and extensive parameter ranges, for differentiation between various ex vivo animal tissue types and identification of prostate cancer in ex vivo human prostate [33], [37], [46]. We plan to extend this study to assess the effect of various ultrasound transducers.…”

Monitoring of Tissue Ablation Using Time Series of Ultrasound RF Data

“…Finally, the area under the ROC curve for the RF time series features is close to 1 compared to 0.8 for spectral features. Previously, it was shown that temperature rise produced by acoustic propagation may be the major contributor to the ability of time series analysis for tissue typing [7]. In other words, the speed of acoustic waves in the tissue is dependent on the tissue temperature.…”

Ultrasound tissue classification: a review

“…In the absence of physiologic motion in ex-vivo experiments, the tissue typing characteristics of RF time series were potentially due to the minute temperature changes caused by continuous sonification. The hypothesis was investigated in Daoud et al (2011), Daoud et al (2013). In Imani et al (2013), the RF time series signals prior to, and at the end of the ablation process are analyzed for lesion detection.…”