Normalization and backscatter spectral analysis of human carotid arterial data acquired using a clinical linear array ultrasound imaging system

The risk of plaque rupture in carotid atherosclerotic disease is associated more closely with the composition of plaque rather than the severity of stenosis. The constituents of plaque can be determined from ultrasonic spectral parameters obtained from normalized backscatter tissue data. Calibration of the data is done using echoes off a specular reflector which removes the system response of an ultrasound transducer, Terason™ (Teratech Corporation), from the backscatter data. A reference spectrum study is used to compare specular reflectors based on time domain (echo) and frequency domain (power spectrum, centroid and parabola test) analysis. Nylon and a tissue-mimicking phantom (velocity = 1560 m/s, slope of attenuation = 0.7 dB/cm MHz) have an intermediate acoustic impedance with respect to water and appear good choices as specular reflectors for clinical ultrasound imaging scanners compared to Plexiglas and other higher reflecting materials. A tissue-mimicking phantom is used to correct for attenuation in plaque, diffraction and saturation of electronics of the ultrasound scanner. Autoregressive power spectrum estimation methods are used to extract spectral parameters (spectral slope, y-intercept, midband fit, maximum and minimum power with corresponding frequencies, and integrated backscatter) from calibrated tissue data and linear and quadratic discriminant rules developed for classification of carotid arterial plaque. Regions of interest (n = 64; 64 samples x 8 scan lines with 30 MHz sampling frequency) consisting of 48 fibrous-fibrofatty (Class 1), 11 thrombus-necrotic core (Class 2), and 5 dense calcium (Class 3) areas selected for analysis show that fibrosis can be differentiated from necrosis and calcification. The quadratic discriminant rule identified necrosis with a lower misclassification rate (9.1%) than the linear discriminant rule (18.2%).