Dynamic Cerebral Autoregulation in Subjects with Alzheimer's Disease, Mild Cognitive Impairment, and Controls: Evidence for Increased Peripheral Vascular Resistance with Possible Predictive Value

Abstract

Cerebrovascular dysfunction plays a role not only in vascular causes of cognitive impairment but also in Alzheimer's disease (AD). We hypothesized that cerebral autoregulation is impaired in patients with AD compared to subjects with mild cognitive impairment (MCI) and controls. Dynamic cerebral autoregulation (dCA) was investigated in 17 AD patients, 19 MCI subjects, and 20 controls (C). Groups were matched for age, gender, and level of education. Electrocardiogram and non-invasive finger arterial blood pressure were measured and transcranial doppler ultrasonography was used to measure cerebral blood flow velocity in right and left middle cerebral artery (MCA). Cerebrovascular resistance index (CVRi) was also computed. dCA in supine position was quantified based on spontaneous blood pressure variations by computation of the linear transfer function between arterial blood pressure and MCA cerebral blood flow velocity. dCA gain and phase were evaluated for different frequency bands. Results were also evaluated using a 3-parameter windkessel model (WKM). CVRi was significantly higher in AD (2.9 ± 0.2) compared to both MCI (2.3 ± 0.1, p = 0.02) and C (2.1 ± 0.1 mmHgs/cm, p = 0.002). Five MCI patients who converted to AD during the course of the study also had higher CVRi compared to non-converters (2.8 ± 0.6 versus 2.1 ± 0.5 mmHgs/cm, p < 0.05). No significant differences in dCA gain and phase were found. In terms of the WKM approach, in the order C→MCI→AD groups showed about equal arterial resistance and peripheral compliance, but increased peripheral vasculature resistance (26 ± 2 versus 36 ± 3 mmHgs/ml in C resp. AD, p = 0.004). In conclusion, AD patients compared to MCI patients and controls have increased CVRi, whereas dCA parameters do not seem to differentiate AD patients. For MCI patients, CVRi might have predictive value in developing AD.

Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis

“…This point is consistent with the developing evidence implicating the impairment of the DCA-DVR process in vascular dementia, Alzheimer’s Disease (AD), and mild cognitive impairment (MCI) [1, 6, 10]. These observations have motivated efforts to develop models that can aid in both advancing our quantitative understanding of the DCA-DVR process and providing effective diagnostic tools capable of reliably detecting the onset of DCA-DVR impairment [6, 16, 19, 22–27]. In input-output modeling studies, subject-specific quantification of DCA is typically based on beat-to-beat measurements of mean arterial blood pressure (MABP) as the input and cerebral blood flow velocity (CBFV) as the output [6, 17, 18].…”

“…The effectiveness of both regulatory processes can diminish with age, supposedly as a result of the degeneration of neurovascular components serving the neurovascular unit [3, 5]. This point is consistent with the developing evidence implicating the impairment of the DCA-DVR process in vascular dementia, Alzheimer’s Disease (AD), and mild cognitive impairment (MCI) [1, 6, 10]. These observations have motivated efforts to develop models that can aid in both advancing our quantitative understanding of the DCA-DVR process and providing effective diagnostic tools capable of reliably detecting the onset of DCA-DVR impairment [6, 16, 19, 22–27].…”

“…These observations have motivated efforts to develop models that can aid in both advancing our quantitative understanding of the DCA-DVR process and providing effective diagnostic tools capable of reliably detecting the onset of DCA-DVR impairment [6, 16, 19, 22–27]. In input-output modeling studies, subject-specific quantification of DCA is typically based on beat-to-beat measurements of mean arterial blood pressure (MABP) as the input and cerebral blood flow velocity (CBFV) as the output [6, 17, 18]. In addition, arterial CO 2 tension, approximated from measurements of end-tidal CO 2 (ETCO2), is often included as a second input in order to assess DVR [7, 9, 13–14, 22–27].…”

“…One commonly used class of parametric models is the lumped-parameter hemodynamic model in the form of RC circuits [6, 8–9, 11–14, 17–18, 21]. In this approach, the cerebral circulation is represented as a series of vascular compartments each representing the cerebral arterial, arteriolar, capillary, and venous segments within the cranium.…”

Assessment of dynamic cerebral autoregulation and cerebrovascular CO2 reactivity in ageing by measurements of cerebral blood flow and cortical oxygenation

“…It is known that arterial walls become thicker and stiffer and vascular elasticity diminishes with ageing, thereby increasing vascular resistance (Lakatta & Levy, 2003;Monahan, 2007;O'Rourke & Hashimoto, 2007). Indeed, Gommer et al (2012) found that higher peripheral vascular resistance correlated with higher CVRi. In the present study, we did not measure absolute cerebral blood flow (in millilitres per minute per 100 g of brain tissue) and we are therefore unable to differentiate between these two explanations for the increased CVRi.…”