Two-Dimensional Sonoelastographic Shear Velocity Imaging

Abstract

We introduce a novel 2-D sonoelastographic technique for estimating local shear velocities from propagating shear wave interference patterns (termed crawling waves) in this paper. A relationship between the local crawling wave spatial phase derivatives and local shear wave velocity is derived, with phase derivatives estimated using a 2-D autocorrelation technique. Comparisons were made between the 2-D sonoelastographic shear velocity estimation technique and its computationally simpler 1-D precursor. In general, the 2-D sonoelastographic shear velocity estimator outperformed the 1-D–based technique in terms of accuracy and estimator noise minimization. For both approaches, increasing the estimator kernel size reduces noise levels but lowers spatial resolution. Homogeneous elastic phantom results demonstrate the ability of sonoelastographic shear velocity imaging to quantify the true underlying shear velocity distributions as verified using time-of-flight measurements. Results also indicate that increasing the estimator kernel size increases the transition zone length about boundaries in heterogeneous elastic mediums and may complicate accurate quantification of smaller elastically contrasting lesions. Furthermore, analysis of contrast-to-noise ratio (CNR) values for sonoelastograms obtained in heterogeneous elastic phantoms reveal that the 2-D sonoelastographic shear velocity estimation technique outperforms the 1-D version for a given kernel size in terms of image noise minimization and contrast enhancement. Experimental results from an embedded porcine liver specimen with a radiofrequency ablation (RFA) lesion demonstrates that the 2-D sonoelastographic shear velocity estimation technique minimizes image noise artifacts and yields a consistent lesion boundary when compared with gross pathology. Volume measurements of the RFA lesion obtained from shear velocity sonoelastograms was comparable to that obtained by fluid displacement of the dissected lesion as illustrated by 3-D volume reconstructions. Overall, 2-D sonoelastographic shear velocity imaging was shown to be a promising new approach to characterizing the shear velocity distribution of elastic materials. (E-mail: hoyt@ece.rochester.edu)