Development and Evaluation of a Multifrequency Ultrafast Doppler Spectral Analysis (MFUDSA) Algorithm for Wall Shear

Andrew J Malone1,2, Seán Cournane3, Izabela Naydenova1

  • 1School of Physics, Clinical and Optometric Sciences, IEO Centre, Faculty of Science and Health, Technological University Dublin, D07 H6K8 Dublin, Ireland.

Insights

A new Multifrequency ultrafast Doppler spectral analysis (MFUDSA) algorithm improves wall shear stress (WSS) measurement in atherosclerotic plaque. This offers potential for earlier cardiovascular disease diagnosis compared to existing methods.

Area of Science:

  • Biomedical Engineering
  • Cardiovascular Imaging
  • Medical Diagnostics

Background:

  • Cardiovascular diseases are a leading cause of death globally.
  • Current diagnostic methods primarily focus on vessel anatomy, potentially missing early disease indicators.
  • Wall shear stress (WSS) is an emerging biomarker for early atherosclerotic disease detection.

Purpose of the Study:

  • To introduce and validate a novel algorithm, Multifrequency ultrafast Doppler spectral analysis (MFUDSA), for quantifying WSS in atherosclerotic plaque.
  • To compare the performance of MFUDSA against existing WSS assessment techniques.
  • To evaluate the potential of MFUDSA for earlier cardiovascular disease diagnosis.

Main Methods:

  • Development and optimization of the MFUDSA algorithm using simulations and in-vitro flow phantom experiments.
  • Comparison of MFUDSA with standard pulsed-wave Doppler, Ultrafast Doppler, Parabolic Doppler, and plane-wave Doppler.
  • Assessment of signal-to-noise ratio (SNR) and velocity resolution improvements.

Main Results:

  • MFUDSA demonstrated a 4-8 fold increase in SNR and a 1.10-1.35 fold increase in velocity resolution compared to 1D Fourier analysis.
  • MFUDSA significantly differentiated WSS values between moderate (p = 0.003) and severe (p = 0.001) disease progression.
  • The algorithm showed superior performance in WSS assessment.

Conclusions:

  • MFUDSA is a promising novel algorithm for accurate WSS quantification in atherosclerotic plaque.
  • The enhanced performance of MFUDSA suggests its potential for earlier and more precise cardiovascular disease diagnosis.
  • This technique may offer advantages over current anatomical imaging methods for risk stratification.

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