The influence of calculation method on estimates of cerebral critical closing pressure.

The critical closing pressure (CrCP) of cerebral circulation is normally estimated by extrapolation of instantaneous velocity-pressure curves. Different methods of estimation were analysed to assess their robustness and reproducibility in both static and dynamic applications. In ten healthy subjects (mean ± SD age 37.5 ± 9.2 years) continuous recordings of arterial blood pressure (BP, Finapres) and bilateral cerebral blood flow velocity (transcranial Doppler ultrasound, middle cerebral arteries) were obtained at rest. Each session consisted of three separate 5 min recordings. A total of four recording sessions for each subject took place over a 2 week period. A total of 117 recordings contained 34 014 cardiac cycles. For each cardiac cycle, CrCP and resistance-area product (RAP) were estimated using linear regression (LR), principal component analysis (PCA), first harmonic fitting (H1), 2-point systolic/diastolic values (2Ps) and 2-point mean/diastolic values (2Pm). LR and PCA were also applied using only the diastolic phase (LRd, PCAd). The mean values of CrCP and RAP for the entire 5 min recording ('static' condition) were not significantly different for LRd, PCAd, H1 and 2Pm, as opposed to the other methods. The same four methods provided the best results regarding the absence of negative values of CrCP and the coefficient of variation (CV) of the intra-subject standard error of the mean (SEM). On the other hand, 'dynamic' applications, such as the transfer function between mean BP and RAP (coherence and RAP step response) led to a different ranking of methods, but without significant differences in CV SEM coherence. For the CV of the RAP step response though, LRd and PCAd performed badly. These results suggest that H1 or 2Pm perform better than LR analysis and should be used for the estimation of CrCP and RAP for both static and dynamic applications.

Spontaneous fluctuations in cerebral blood flow regulation: contribution of PaCO2.

To investigate the temporal variability of dynamic cerebral autoregulation (CA), the transient response of cerebral blood flow to rapid changes in arterial blood pressure, a new approach was introduced to improve the temporal resolution of dynamic CA assessment. Continuous bilateral recordings of cerebral blood flow velocity (transcranial Doppler, middle cerebral artery), end-tidal Pco(2) (Pet(CO(2)), infrared capnograph), and blood pressure (Finapres) were obtained at rest and during breath hold in 30 young subjects (25 ± 6 yr old) and 30 older subjects (64 ± 4 yr old). Time-varying estimates of the autoregulation index [ARI(t)] were obtained with an autoregressive-moving average model with coefficients expanded by orthogonal decomposition. The temporal pattern of ARI(t) varied inversely with Pet(CO(2)), decreasing with hypercapnia. At rest, ARI(t) showed spontaneous fluctuations that were significantly different from noise and significantly correlated with spontaneous fluctuations in Pet(CO(2)) in the majority of recordings (young: 72% and old: 65%). No significant differences were found in ARI(t) due to aging. This new approach to improve the temporal resolution of dynamic CA parameters allows the identification of physiologically meaningful fluctuations in dynamic CA efficiency at rest and in response to changes in arterial CO(2).

Continuous estimates of dynamic cerebral autoregulation during transient hypocapnia and hypercapnia.

Dynamic cerebral autoregulation (CA) is the transient response of cerebral blood flow (CBF) to rapid blood pressure changes: it improves in hypocapnia and becomes impaired during hypercapnia. Batch-processing techniques have mostly been used to measure CA, providing a single estimate for an entire recording. A new approach to increase the temporal resolution of dynamic CA parameters was applied to transient hypercapnia and hypocapnia to describe the time-varying properties of dynamic CA during these conditions. Thirty healthy subjects (mean +/- SD: 25 +/- 6 yr, 9 men) were recruited. CBF velocity was recorded in both middle cerebral arteries (MCAs) with transcranial Doppler ultrasound. Arterial blood pressure (Finapres), end-tidal CO(2) (ET(CO(2)); infrared capnograph), and a three-lead ECG were also measured at rest and during repeated breath hold and hyperventilation. A moving window autoregressive moving average model provided continuous values of the dynamic CA index [autoregulation index (ARI)] and unconstrained gain. Breath hold led to significant increase in ET(CO(2)) (+5.4 +/- 6.1 mmHg), with concomitant increase in CBF velocity in both MCAs. Continuous dynamic CA parameters showed highly significant changes (P < 0.001), with a temporal pattern reflecting a delayed dynamic response of CA to changes in arterial Pco(2) and a maximal reduction in ARI of -5.1 +/- 2.4 and -5.1 +/- 2.3 for the right and left MCA, respectively. Hyperventilation led to a marked decrease in ET(CO(2)) (-7.2 +/- 4.1 mmHg, P < 0.001). Unexpectedly, CA efficiency dropped significantly with the inception of the metronome-controlled hyperventilation, but, after approximately 30 s, the ARI increased gradually to show a maximum change of 5.7 +/- 2.9 and 5.3 +/- 3.0 for the right and left MCA, respectively (P < 0.001). These results confirm the potential of continuous estimates of dynamic CA to improve our understanding of human cerebrovascular physiology and represent a promising new approach to improve the sensitivity of clinical applications of dynamic CA modeling.