Relations of impaired blood flow and cerebrospinal fluid flow with damage of strategic for cognitive impairment brain regiones in cerebral small vessel disease

Abstract

Introduction. Cerebral small vessel disease (CSVD), associated with age and vascular risk factors, as well as the main cause of vascular and degenerative mixed cognitive impairment (CI). Previously established microstructural predictors of CI (axial diffusion in normal-appearing periventricular white matter of the posterior left frontal lobe, the right midcingulate cortex, and the middle posterior part of the corpus callosum) can be used to calculate an integrative factor, exceeding the threshold value for which indicates the presence of CI. The use of this factor in the diagnosis of CI in CSVD is supported by the fact that leading mechanisms of CSVD are involved in the damage to areas of the brain that are strategic for CI. The aim of this study was to clarify the link between the known microstructural predictors of CI in CSVD and MRI findings that correspond to the main mechanisms of CSVD. Materials and methods. Patients (n = 74; including 48 women; average age 60.6 6.9 years) with CSVD and CI of varying severity underwent phase-contrast MRI and voxel-based morphometry (3T) to assess arterial, venous and CSF flow, as well as atrophy. Results. The established microstructural predictors of CI correlated with measures of arterial and venous blood flow, as well as atrophy. Linear regression models allow us to estimate cognitive impairment (CI) predictors in cerebral small vessel disease (CSVD), based on increased arterial velocity pulse index, CSF flow at the level of the cerebral aqueduct, cerebral aqueduct area and lateral ventricles volume, when there is reduced blood flow in the superior sagittal sinus and the overall arterial blood flow. Conclusion. The ability to calculate microstructural predictors of CI due to CSVD, based on MRI findings, indicates the validity of using an integrative measure of microstructural predictors of CI as a diagnostic tool of CI in CSVD.