Optimising the assessment of cerebral autoregulation from black box models

Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and non-linear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single – or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end 26 recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a ‘gold’ standard for the study of dynamic CA, lower inter- and intra-subject variability of the parameters in relation to the difference between normo- and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies

Assessing blood flow control through a bootstrap method

In order to assess blood flow control, the relationship between blood pressure and blood flow can be modeled by linear filters. We present a bootstrap method, which allows the statistical analysis of an index of blood flow control that is obtained from constrained system identification using an established set of pre-defined filters

Optimising the assessment of cerebral autoregulation from black box models

Cerebral autoregulation (CA) mechanisms maintain blood flow approximately stable despite changes in arterial blood pressure. Mathematical models that characterise this system have been used extensively in the quantitative assessment of function/impairment of CA. Using spontaneous fluctuations in arterial blood pressure (ABP) as input and cerebral blood flow velocity (CBFV) as output, the autoregulatory mechanism can be modelled using linear and non-linear approaches, from which indexes can be extracted to provide an overall assessment of CA. Previous studies have considered a single – or at most a couple of measures, making it difficult to compare the performance of different CA parameters. We compare the performance of established autoregulatory parameters and propose novel measures. The key objective is to identify which model and index can best distinguish between normal and impaired CA. To this end 26 recordings of ABP and CBFV from normocapnia and hypercapnia (which temporarily impairs CA) in 13 healthy adults were analysed. In the absence of a ‘gold’ standard for the study of dynamic CA, lower inter- and intra-subject variability of the parameters in relation to the difference between normo- and hypercapnia were considered as criteria for identifying improved measures of CA. Significantly improved performance compared to some conventional approaches was achieved, with the simplest method emerging as probably the most promising for future studies

A parametric approach to measuring cerebral blood flow autoregulation from spontaneous variations in blood pressure

Autoregulation maintains cerebral blood flow (CBF) almost constant in the face of changes in arterial blood pressure (ABP). Tests for impairment of this process using only spontaneous fluctuations in ABP, without provoking large variations, are of great clinical interest, and a range of different approaches have previously been applied. Extending earlier work based on linear filters, we propose a simple parametric method using a first order finite impulse response filter. We evaluate the method on ABP and CBF velocity [(CBFV), from trancranial Doppler ultrasound] signals collected in 60 patients with stenosis or occlusion of the carotid arteries. Data were collected during the inspiration of ambient air, a 5% CO2/air mixture, and finally the return to ambient air. Equivalent data were collected in 15 normal subjects. The filters estimated from the data segments with constant inspiratory pCO2 showed the expected high-pass characteristic, which was reduced during hypercapnia and also in patients. Highly significant correlation between the filter parameters and cerebrovascular reactivity (percent increase in CBFV per unit change in end-tidal pCO2) gives further evidence that the filters reflect autoregulation. The method allows simple parametrization of the dynamic autoregulatory responses in CBFV, and the analysis of short (1 min) data segments