Modified Continuous Wavelet Transform Estimator for Crawling Waves Sonoelastography Using Normal Propagation

Abstract

Crawling Waves Sonoelastography (CWS) is a quantitative ultrasound elastography technique that uses an interference pattern to estimate the Shear Wave Speed (SWS) which is related to tissue stiffness. This technique requires vibration sources to generate a mechanical reaction in soft tissue and depends on the location of the mechanical sources, elastography approach is obtained. There are a set of different methods to estimate the SWS values. However, many of them are designed for a parallel propagation which is difficult to generate the tissue movement in clinical practice. In this regard, an alternative normal propagation have been previously proposed for it evaluation and it can be more applicable approach to in vivo analysis due the location of the vibration sources placed on the top of the surface. A previous estimator based on Phase Derivative (PD) has been modified to apply it with a normal setup, however, results in phantom studies suggest the presence of artifacts in the SWS map that generate bad discrimination of the regions. In this study, an estimator based on Continuous Wavelet Transform (CWT) is modified for normal propagation and the performance is evaluated with heterogeneous phantom studies and compared with results obtained with PD estimator. SWS values were obtained for the two estimator within a region of interest for the background (At 300 Hz, TOF: 3.45 m/s, CWT: 3.49 ± 0.37 m/s, PD: 3.95 ± 0.24 m/s) and in the inclusion (At 300 Hz, TOF: 5.1 m/s CWT: 4.89 ± 0.13 m/s, PD: 4.37 ± 0.39 m/s). To evaluate the capability of the estimators to discriminate between regions two metrics were taken into consideration: contrast-to-noise ratio and contrast ratio. The results show that the modified CWT estimator presents higher accuracy and the differentiation of regions will be better with this estimator. Clinical relevance — This study presents a modified continuous wavelet transform estimator for Crawling Wave Sonoelastography. This algorithm can be useful to provide tissue stiffness information for diagnosis or monitoring of tissue pathologies.