Cerebral autoregulation is the ability of the brain to maintain a relatively constant blood flow during changes in cerebral perfusion pressure (CPP) or arterial blood pressure (ABP). Continuous indices of cerebral autoregulation can be calculated from spontaneous fluctuations of CPP or ABP and cerebral blood flow velocity (FV) using ICM+.
Mean flow index (Mx and Mxa)
Transcranial Doppler (TCD) -based continuous indices of autoregulation measurement have been readily described within the scientific literature. One of the most common TCD indices is the mean flow index, derived from the moving correlation coefficient between: mean flow velocity (FVm) and CPP (producing Mx), or ABP (producing Mxa). Numerous publications have emerged on Mx and Mxa, linking either to outcome in traumatic brain injury. Mx/Mxa close to +1 denotes that slow fluctuations in ABP produce synchronised slow changes in FV, indicating defective cerebral autoregulation. Thresholds associated with patient outcome have even been defined for Mx, quoting thresholds of +0.05 and +0.30 for mortality and unfavourable functional outcome at 6 months, respectively. Furthermore, Mx has displayed a moderate correlation to the commonly-employed ICP derived index, pressure reactivity index (PRx), with a correlation coefficient of 0.58.
Cerebral autoregulation index (ARI)
Cerebral autoregulation can also be assessed using the autoregulation index (ARI), a dimensionless index ranging from 0 to 9, for which a response of FV to a hypothetical impulse change in ABP is estimated using transfer function analysis of spontaneous fluctuations in ABP and FV. An ARI of 9 describes a system in which CBF returns quickly to baseline levels after step-changes in ABP; an ARI value of 0 describes a system in which there is no compensatory change in CBF, indicating completely impaired cerebral autoregulation. On this scale, normal autoregulatory capacity is defined as an ARI of 4 to 7, abnormal 3 and below. On ICM+ ARI is implemented as an in-built function, in which FV changes recorded during the step change in ABP are normalised and compared to 10 grades (0-9) to determine which model response constitutes the best fit, and the grade of that response is returned as ARI.