The role of arterial, venous blood and cerebrospinal fluid flow disturbances in forming cognitive impairment types in age-related cerebral microangiophathy

Abstract

Age-related cerebral microangiopathy (small vessel disease, SVD) is the main cause of vascular and mixed cognitive impairment (CI) with a complex neuropsychological profile. To investigate the role of arterial and venous blood flow and cerebrospinal fluid (CSF) flow, as well as their interrelation, in the forming of CI types in patients with SVD. Fifty patients (31 f., mean age 61.2±6,2) with SVD (STRIVE, 2013), including 37 with mild CI and 13 with dementia, were examined. A type of CI was determined based on combination of standard deviations from normal results on memory and executive function tests: isolated dysexecutive (13) and predominantly dysexecutive (6), predominantly amnestic (12), mixed, equal impairment of EF and memory, (19). In the statistical analysis, groups of the isolated and predominantly dysexecutive types were merged according to the dominance of deviations in the EF into the dysexecutive type of CI (19). Phase contrast MRI (PhC-MRI) was used to assess characteristics of arterial and venous blood flow and CSF flow on different levels. Indexes of pulse and intracranial compliance and surface of the cerebral aqueduct were calculated. Patients with all CI types had a CSF flow systolic peak delay at the cervical level. Mixed and dysexecutive CI types as compared with predominantly amnestic type and control were defined by blood flow reduction in the sinus rectus, and mixed type by the additional decrease in its pulse wave width, blood flow reduction in an internal jugular artery and maximal blood flow velocity in the inner carotid artery, the increase in the intracranial compliance index and surface of the cerebral aqueduct. The neuropsychological CI type in SVD is defined by features of pathophysiological mechanisms conditioned on differences in blood flow and CSF flow impairment severity and formed hydrodynamic interaction between them. Differential features of CI types in SVD defined by PhC-MRI might become important predictive indicators of potential interaction between SVD and degeneration, improve understanding of risk factors, pathogenesis, prevention and treatment of age-related brain damage.