"Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers"
October 1, 2021
A paper co-authored by PhD students Jihye Baek and Sedigheh Poul, and Professor Kevin Parker titled "Clusters of ultrasound scattering parameters for the classification of steatotic and normal livers" has been published in Ultrasound in Medicine and Biology. Co-authors include collaborators from the University of Texas at Dallas (Kenneth Hoyt, Lokesh Basavarajappa, Shreya Reddy, and Haowei Tai). The abstract follows; more information can be found here.
Abstract: The study of ultrasound tissue interactions in fatty livers has a long history with strong clinical potential for assessing steatosis. Recently we proposed alternative measures of first- and second-order statistics of echoes from soft tissues, namely, the H-scan, which is based on a matched filter approach, to quantify scattering transfer functions and the Burr distribution to model speckle patterns. Taken together, these approaches produce a multiparameter set that is directly related to the fundamentals of ultrasound propagation in tissue. To apply this approach to the problem of assessing steatotic livers, these analyses were applied to in vivo rat livers (N=21) under normal feeding conditions or after receiving a methionine- and choline-deficient diet that produces steatosis within a few weeks. Ultrasound data were acquired at baseline and again at weeks 2 and 6 before applying the H-scan and Burr analyses. Furthermore, a classification technique known as the support vector machine was then used to find clusters of the five parameters that are characteristic of the different steatotic liver conditions as confirmed by histologic processing of excised liver tissue samples. With the in vivo multiparametric ultrasound measurement approach and determination of clusters, steatotic can be discriminated from normal livers with 100% accuracy in a rat animal model.