Microembolic signal description: a reappraisal based on a customized digital postprocessing system

W H Mess1, J M Willigers, L A F Ledoux

  • 1Department of Clinical Neurophysiology, Maastricht University, Maastricht, The Netherlands. Max@fknf.azm.nl

Insights

New analysis of microembolic signals (MES) using radiofrequency (RF) data from transcranial Doppler sonography (TCD) reveals consistent patterns. This advanced processing clarifies MES signatures in the middle cerebral artery (MCA), reducing variability seen in conventional methods.

Area of Science:

  • Neurosonology
  • Biomedical Engineering
  • Medical Imaging

Background:

  • Microembolic signals (MES) detected via transcranial Doppler sonography (TCD) in the middle cerebral artery (MCA) exhibit high variability.
  • Existing data do not fully explain the diverse presence and signatures of MES.

Purpose of the Study:

  • To investigate the underlying patterns of microembolic signals (MES) using advanced radiofrequency (RF) signal processing.
  • To explain the variability in MES detection observed with conventional transcranial Doppler sonography (TCD) systems.

Main Methods:

  • Applied customized postprocessing to the radiofrequency (RF) signal of a standard TCD system.
  • Utilized spatial resolution of approximately 2 mm and plotted clutter-filtered RF signal amplitude over time and depth.
  • Performed 128-point Fast Fourier Transforms (FFTs) to visualize background Doppler spectrum and MES.
  • Analyzed 122 gaseous MES during cardiac surgery and 52 particulate MES after carotid endarterectomy.

Main Results:

  • Both gaseous and particulate MES displayed consistent signatures as straight lines of increased intensity in RF amplitude plots.
  • MES velocity remained constant within the ultrasound beam and did not exceed background Doppler spectrum velocity.
  • Identified distinct MES patterns based on depth, with some gaseous MES changing direction, suggesting vessel branching.
  • FFT analysis revealed MES containing both positive and negative frequencies.

Conclusions:

  • Microembolic signals (MES) exhibit consistent signature patterns in amplitude-time plots when analyzed with advanced RF signal processing.
  • The previously reported variability in MES detection using conventional Doppler systems is likely an artifact of larger signal amplitudes and sample volumes.

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