Quantifying cerebral autoregulation following endovascular thrombectomy using wavelet transformation.

Area of Science:

• Neuroscience
• Cardiovascular Medicine
• Medical Imaging

Background:

• Cerebral autoregulation (CA) is crucial for maintaining stable cerebral blood flow (CBF), especially in acute ischemic stroke (AIS) patients.
• Endovascular thrombectomy (EVT) is a key treatment for AIS, but its impact on CA requires further investigation.
• Continuous wavelet transform (CWT) offers a robust method for quantifying CA, yet data post-EVT are limited.

Purpose of the Study:

• To characterize CA using CWT in AIS patients following EVT.
• To explore the relationship between CWT-derived CA metrics and clinical outcomes after EVT.

Main Methods:

• A prospective observational study included 20 AIS patients treated with EVT.
• Transcranial Doppler ultrasound (TCD) measured middle cerebral artery (MCA) blood flow velocities, synchronized with arterial blood pressure (ABP).
• CWT-derived Synchronization index gamma (SI) was calculated in the very-low frequency range (0.005-0.08 Hz).

Main Results:

• No significant difference in median SI was found between favorable and unfavorable 90-day outcomes (p=0.055).
• Higher median SI was observed in patients without early neurological recovery (p=0.005), indicating impaired CA.
• Median SI inversely correlated with ASPECTS (rho=-0.52, p=0.043), suggesting poorer CA with larger infarcts.

Conclusions:

• CWT is a feasible method for assessing CA in AIS patients post-EVT.
• CWT-derived metrics may offer valuable insights into early cerebral hemodynamics after arterial recanalization.