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Updated: Jul 24, 2026

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
Published on: June 16, 2014
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
Abstract:
The high variability in presence and signature of microembolic signals (MES), detected with transcranial Doppler sonography (TCD) in the middle cerebral artery (MCA), cannot be explained with the currently available published data. We applied customized postprocessing on the radiofrequency (RF) signal of a standard TCD system. The spatial resolution was on the order of 2 mm, depending only on the length of the ultrasound (US) burst emitted. The amplitude of clutter-filtered RF signals was color-coded and plotted as a function of time and depth (range 30 mm). Additionally, 128 point fast Fourier transforms (FFTs) (50% temporal overlap) were calculated, visualizing both the background Doppler spectrum and the MES. We evaluated 122 gaseous MES from two patients during cardiac surgery and 52 particulate MES from four patients after carotid endarterectomy. Both MES categories showed comparable properties: they appeared in the RF amplitude plot as rather straight lines of increased intensity, indicating that the velocity remained approximately the same while they passed the US beam. The velocity calculated from the amplitude plot never exceeded that of the background Doppler spectrum. Various "MES patterns" could be identified with respect to the depth range at which the MES were visible. A quarter of the gaseous MES changed their direction at a specific depth, suggesting that the MES entered a branch (e.g., an M2 artery or the anterior cerebral artery). In the FFT analysis, these MES contained both positive and negative frequencies. It is concluded that MES show consistent signature patterns in the amplitude-time plots and that the previously reported variability of MES appearance in conventional Doppler systems is an artefact caused by relatively large signal amplitudes and sample volumes.
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.

