Spectral analysis of ultrasound backscatter for non-invasive measurement of plaque composition

Carotid atherosclerotic plaque composition may be an important indication of patient risk for future cerebro-vascular events. Ultrasound spectral analysis has the potential to provide a robust measure of plaque composition in vivo if the backscatter transfer function can be sufficiently isolated from the effects of attenuation from overlying tissue, receive and transmit transfer functions from the ultrasound system and transducer, and diffraction. This study examines the usefulness of the nonlinearly generated second harmonic portion of the backscatter signal and the effects of a variety of attenuation compensation techniques for noninvasively char-acterizing human carotid plaque using spectral analysis and machine learning. Post-beamformed ultrasound backscatter radiofrequency (RF) data were acquired from 6 normal subjects and 119 carotid endarterectomy patients prior to surgery. Plaque obtained following surgery was histologically processed, and regions of interest (ROI) corresponding to homogenous tissue types (fibrous/fibro-lipidic, hemorrhagic and/or necrotic core and calcified) were selected from RF data. Both the harmonic and fundamental power spectra for each ROI was obtained and normalized by data from a uniform phantom (0.5 dB/cm-MHz slope of attenuation). Additional attenuation compensation approaches were compared to simply using the reference phantom: (1) optimum power spectral shift estimation, (2) one-step adventitial, or (3) two-step adventitial. Spectral parameters extracted from both the fundamental and harmonic estimates of the backscatter transfer function of 363 ROI's from 152 plaque specimens were used to train and test random forest and support vector machine classification models. The best results came from using spectral parameters derived from both the fundamental and second harmonic bands with a predictive accuracy of 65-68%, kappa statistic of 0.49-0.54, and accuracies of 84% for fibrous, 68-74% for hemorrhagic and/or necrotic core, and 78-81% for calcified ROI's. The result indicated that the nonlinearly generated second harmonic portion of backscatter is useful for carotid plaque tissue character-ization and that a reference phantom approach with a 0.5 dB/cm-MHz slope of attenuation works as well as more complicated approaches.

Automated summary

Carotid atherosclerotic plaque composition can predict the risk of future cerebrovascular events. This study explores the use of ultrasound spectral analysis and machine learning for noninvasive characterization of carotid plaque, focusing on the nonlinearly generated second harmonic portion of the backscatter signal. The results indicate that this approach is effective for tissue characterization and that a reference phantom with attenuation slope of 0.5 dB/cm-MHz works as well as more complex methods.