Challenges in Tissue Characterization from Backscattered Intravascular Ultrasound Signals

Plaque characterization through backscattered intravascular ultrasound (IVUS) signal analysis has been the subject of extensive study for the past several years. A number of algorithms to analyze IVUS images and underlying RF signals to delineate the composition of atherosclerotic plaque have been reported. In this paper, we present several realistic challenges one faces throughout the process of developing such algorithms to characterize tissue type. The basic tenet of ultrasound tissue characterization is that different tissue types imprint their own "signature" on the backscattered echo returning to the transducer. Tissue characterization is possible to the extent that these echo signals can be received, the signatures read, and uniquely attributed to a tissue type. The principal difficulty in doing tissue characterization is that backscattered RF signals originating as echoes from different groups of cells of the same tissue type exhibit no obvious commonality in appearance in the time domain. This happens even in carefully controlled laboratory experiments. We describe the method of acquisition and digitization of ultrasound radiofrequency (RF) signals from left anterior descending and left circumflex coronary arteries. The challenge of obtaining corresponding histology images to match to specific regions-of-interest on the images is discussed. A tissue characterization technique based on seven features is compared to a full spectrum based approach. The same RF and histology data sets were used to evaluate the performances of these two techniques.