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Published on: January 20, 2023
Embolic Doppler ultrasound signal detection using continuous wavelet transform to detect multiple vascular emboli
Him Shing Ng1, Qing Hao, Thomas Leung
1Division of Neurology, Department of Medicine and Therapeutics, Prince of Wales Hospital, Chinese University of Hong Kong, China.
Summary
A new wavelet-based algorithm successfully detected multiple microembolic signals (MESs) in patients, a significant advancement over conventional methods for analyzing stroke-related emboli.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Medical Imaging
Background:
- Ischemic stroke is primarily caused by emboli, which can be solid or gaseous.
- Transcranial Doppler ultrasound detects microembolic signals (MESs), but current methods struggle to differentiate single from multiple emboli.
- Previous in vitro studies developed a wavelet-based algorithm for multiple emboli detection.
Purpose of the Study:
- To investigate the clinical utility of a wavelet-based algorithm for detecting multiple emboli in patients.
- To assess the algorithm's ability to identify complex embolic events previously difficult to observe.
Main Methods:
- Microembolic signals (MESs) were collected from patients undergoing carotid artery stenting and those with middle cerebral artery stenosis.
- Continuous wavelet transform was applied to detect and quantify multiple emboli within the recorded MESs.
Main Results:
- No multiple MESs were identified in 17 MESs recorded from middle cerebral artery stenosis patients.
- The algorithm detected 31 instances of multiple MESs among 306 recorded from carotid stenting patients.
Conclusions:
- Continuous wavelet transform effectively detects and quantifies multiple emboli in clinical settings.
- This advanced technique offers improved observation capabilities compared to conventional analysis methods for embolic signals.
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