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Evaluation of Cerebral Blood Flow Autoregulation in the Rat Using Laser Doppler Flowmetry

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At what data length do cerebral autoregulation measures stabilise?

Adam Mahdi¹, Dragana Nikolic, Anthony A Birch

¹Department of Engineering Science, University of Oxford, Oxford, United Kingdom.

Physiological Measurement

|June 3, 2017

Summary

Determining the minimum data length for stable cerebral autoregulation (CA) analysis is crucial. This study found that the Autoregressive Index (ARI), Mean Arterial Pressure-Cerebral Blood Flow Velocity (Mx), and Phase coefficients stabilize with specific data lengths, impacting CA assessment reliability.

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Area of Science:

Neuroscience
Biomedical Engineering
Physiology

Background:

Cerebral autoregulation (CA) is vital for maintaining stable brain blood flow.
Mathematical models using arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) are common for CA assessment.
Current literature lacks consensus on the minimum data length required for reliable CA coefficient estimation.

Purpose of the Study:

To introduce an empirical tool for determining the minimum time series length for popular CA coefficients.
To investigate the data length requirements for ARI, Mx, and Phase coefficients in the low-frequency range (0.07-0.2 Hz).

Main Methods:

Utilized high-quality, artifact-free baseline ABP-CBFV time series (16 minutes each).
Data were beat-to-beat averaged and downsampled to 10 Hz.
Applied a novel empirical tool to analyze the minimum data length for parameterizing CA coefficients.

Main Results:

The Autoregressive Index (ARI) demonstrated higher variability in shorter intervals but stabilized the quickest.
Mx and Phase coefficients showed less variability in short intervals compared to ARI.
Minimum data lengths were identified for stable estimation of ARI, Mx, and Phase.

Conclusions:

Estimating ARI, Mx, and Phase on intervals shorter than 3, 6, and 5 minutes, respectively, can lead to high sensitivity to data length.
These findings provide critical guidance for standardizing CA analysis duration.
Reliable CA assessment necessitates adherence to identified minimum data lengths for each coefficient.