Reduced-order modeling and analysis of dynamic cerebral autoregulation via diffusion maps.

Objective.A data-driven technique for parsimonious modeling and analysis of dynamic cerebral autoregulation (DCA) is developed based on the concept of diffusion maps. Specifically, first, a state-space description of DCA dynamics is considered based on arterial blood pressure, cerebral blood flow velocity, and their time derivatives. Next, an eigenvalue analysis of the Markov matrix of a random walk on a graph over the dataset domain yields a low-dimensional representation of the intrinsic dynamics. Further dimension reduction is made possible by accounting only for the two most significant eigenvalues. The value of their ratio indicates whether the underlying system is governed by active or hypoactive dynamics, indicating healthy or impaired DCA function, respectively. We assessed the reliability of the technique by considering healthy individuals and patients with unilateral internal carotid artery (ICA) stenosis or occlusion. We computed the sensitivity of the technique to detect the presumed side-to-side difference in the DCA function of the second group (assuming hypoactive dynamics on the occluded or stenotic side), using McNemar's chi square test. The results were compared with transfer function analysis (TFA). The performance of the two methods was also compared under the assumption of missing data.Main results.Both diffusion maps and TFA suggested a physiological side-to-side difference in the DCA of ICA stenosis or occlusion patients with a sensitivity of 81% and 71%, respectively. Further, both two methods suggested the difference between the occluded or stenotic side and any two sides of the healthy group. However, the diffusion maps captured additional difference between the unoccluded side and the healthy group, that TFA did not. Furthermore, compared to TFA, diffusion maps exhibited superior performance when subject to missing data.Significance.The eigenvalues ratio derived using the diffusion maps technique can be potentially used as a reliable and robust biomarker for assessing how active the intrinsic dynamics of the autoregulation is and for indicating healthy versus impaired DCA function.

Changes on Dynamic Cerebral Autoregulation Are Associated with Delayed Cerebral Ischemia in Patients with Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Early identification of vasospasm prior to symptom onset would allow prevention of delayed cerebral ischemia (DCI) in aneurysmal subarachnoid hemorrhage (aSAH). Dynamic cerebral autoregulation (DCA) is a noninvasive means of assessing cerebral blood flow regulation by determining independence of low-frequency temporal oscillations of systemic blood pressure (BP) and cerebral blood flow velocities (CBFV). METHODS: Eight SAH patients underwent prospectively a median of 7 DCA assessments consisting of continuous measurements of BCFV and BP. Transfer function analysis was applied to calculate average phase shift (PS) in low (0.07-0.2 Hz) frequency range for each hemisphere as continuous measure of DCA. Lower PS indicated poorer regulatory response. DCI was defined as a 2-point decrease in Glasgow Coma Score and/or infarction on CT. RESULTS: Three subjects developed symptomatic vasospasm with median time-to-DCI of 9 days. DCI was significantly associated with lower PS over the entire recording period (Wald = 4.28; p = 0.039). Additionally, there was a significant change in PS over different recording periods after adjusting for DCI (Wald = 15.66; p = 0.001); particularly, a significantly lower mean PS day 3-5 after bleed (14.22 vs 27.51; p = 0.05). CONCLUSIONS: DCA might be useful for early detection of symptomatic vasospasm. A larger cohort study of SAH patients is currently underway.