Assessment of the Thigh Cuff Technique for Measurement of Dynamic Cerebral Autoregulation

Abstract

Background and Purpose —Dynamic methods of measuring cerebral autoregulation have become an accepted alternative to static evaluation. This article aims to describe a set of data collected from healthy volunteers by a dynamic method, the purpose being to qualify and quantify expected results for those who may be designing a study using this technique. Methods —Cerebral blood flow velocity (CBFV) (measured by transcranial Doppler) and arterial blood pressure (Finapres) were recorded in 16 normal subjects before, during, and after the induction of a blood pressure drop (release of bilateral thigh cuffs). This procedure was repeated 6 times for each subject. A mathematical model was applied to the data to generate an autoregulatory index (ARI) with values between 0 and 9. Results —The ARI values for this sample population follow a normal distribution, with a mean±SD of 4.98±1.06 (n=15). Analysis of the cumulative mean ARI values of all subjects showed an exponential-type convergence of ARI toward the sample mean as the number of test iterations increased. The population average blood pressure drop on thigh cuff release was 26.4±7.1 mm Hg (n=16), occurring in 4.6±1.7 seconds. The corresponding population average drop for CBFV was 15.6±5.8 cm/s, taking 2.5±1.0 seconds. No significant trend was noted in the measurements as the number of test iterations increased. The correlation between the predicted and actual CBFV, having a mean value of 0.76±0.19, showed evidence of a nonlinear relationship to ARI values. Significant correlation was also found between ARI and (1) arterial blood pressure before cuff release and (2) the magnitude of the drop in CBFV on cuff release. Conclusions —The distribution of ARI values is not significantly different from normal. At least 3 iterations of the test procedure should be performed and averaged to obtain the mean ARI for each subject. There is no significant evidence of physiological accommodation as the number of test iterations increases. The effects of mean blood pressure and the magnitude of the change in CBFV should be considered as possible covariates when ARI data are analyzed.