Fourier Synchrosqueezed Transform for Shear Wave Speed Estimation in Crawling Wave Sonoelastography Approach

Area of Science:

• Medical Imaging
• Biophysics
• Ultrasound Technology

Background:

• Crawling Wave Sonoelastography (CWS) quantifies tissue stiffness using ultrasound to measure shear wave speed (SWS).
• Previous time-frequency methods for SWS estimation in CWS suffer from limitations like artifacts and blurred maps.

Purpose of the Study:

• To introduce and validate a novel Shear Wave Speed (SWS) estimator for Crawling Wave Sonoelastography (CWS) using the Fourier Synchrosqueezed Transform (FSST).
• To evaluate the performance of the FSST-based SWS estimator compared to existing time-frequency techniques.

Main Methods:

• Implementation of the Fourier Synchrosqueezed Transform (FSST) for SWS estimation in CWS.
• Validation using existing datasets from homogeneous and heterogeneous phantoms with vibration frequencies from 200 to 360 Hz.
• Comparison of performance metrics including SWS mean value, standard deviation, coefficient of variation (CV), Bias, R2080, and contrast-to-noise ratio (CNR).

Main Results:

• The FSST estimator showed marginally superior performance in SWS mean value, CV, and CNR.
• The FSST method demonstrated better performance in Bias and R2080 compared to previous approaches.
• Specific improvements noted at 320 Hz and 340 Hz vibration frequencies in phantom studies.

Conclusions:

• The novel FSST-based SWS estimator offers improved accuracy and reduced artifacts for CWS.
• This technique has potential for real-time tissue elasticity characterization in clinical applications.
• The FSST method enhances the quantitative capabilities of CWS for medical diagnosis.