The evaluation of the clustering of magnetic resonance imaging (MRI) signs into MRI types and their relationship with circulating markers of vascular wall damage were performed in 96 patients with cerebral small vessel disease (cSVD) (31 men and 65 women; mean age, 60.91 ± 6.57 years). The serum concentrations of the tumor necrosis factor-α (TNF-α), transforming growth factor-β1 (TGF-β1), vascular endothelial growth factor-A (VEGF-A), and hypoxia-inducible factor 1-α (HIF-1α) were investigated in 70 patients with Fazekas stages 2 and 3 of white matter hyperintensities (WMH) and 21 age- and sex-matched volunteers with normal brain MRI using ELISA. The cluster analysis excluded two patients from the further analysis due to restrictions in their scanning protocol. MRI signs of 94 patients were distributed into two clusters. In the first group there were 18 patients with Fazekas 3 stage WMH. The second group consisted of 76 patients with WMH of different stages. The uneven distribution of patients between clusters limited the subsequent steps of statistical analysis; therefore, a cluster comparison was performed in patients with Fazekas stage 3 WMH, designated as MRI type 1 and type 2 of Fazekas 3 stage. There were no differences in age, sex, degree of hypertension, or other risk factors. MRI type 1 had significantly more widespread WMH, lacunes in many areas, microbleeds, atrophy, severe cognitive and gait impairments, and was associated with downregulation of VEGF-A compared with MRI type 2. MRI type 2 had more severe deep WMH, lacunes in the white matter, no microbleeds or atrophy, and less severe clinical manifestations and was associated with upregulation of TNF-α compared with MRI type 1. The established differences reflect the pathogenetic heterogeneity of cSVD and explain the variations in the clinical manifestations observed in Fazekas stage 3 of this disease.

Cerebral small vessel disease (SVD) is one of the leading causes of cognitive impairment and stroke. The importance of endothelial dysfunction and high blood–brain barrier (BBB) permeability in pathogenesis, together with ischemia, is under discussion. The aim of this study was to clarify the relationship between tissue plasminogen activator (t-PA), plasminogen activator inhibitor (PAI-1), and magnetic resonance imaging (MRI) signs of SVD. We examined 71 patients (23 men and 48 women; mean age: 60.5 ± 6.9 years) with clinical and MRI signs of SVD, and 21 healthy volunteers with normal MRIs. All subjects underwent 3T MRI and measurements of t-PA and PAI-1 levels. An increase in t-PA level is correlated with the volume of white matter hyperintensities (WMH) (R = 0.289, p = 0.034), severity on the Fazekas scale (p = 0.000), and with the size of subcortical (p = 0.002) and semiovale (p = 0.008) perivascular spaces. The PAI-1 level is not correlated with the t-PA level or MRI signs of SVD. The correlation between t-PA and the degree of WMH and perivascular spaces’ enlargement, without a correlation with PAI-1 and lacunes, is consistent with the importance of t-PA in BBB disruption and its role in causing brain damage in SVD.

Introduction: Cerebral small vessel disease (CSVD) is the leading cause of vascular and mixed degenerative cognitive impairment (CI). The variability in the rate of progression of CSVD justifies the search for sensitive predictors of CI. Materials: A total of 74 patients (48 women, average age 60.6 ± 6.9 years) with CSVD and CI of varying severity were examined using 3T MRI. The results of diffusion tensor imaging with a region of interest (ROI) analysis were used to construct a predictive model of CI using binary logistic regression, while phase-contrast magnetic resonance imaging and voxel-based morphometry were used to clarify the conditions for the formation of CI predictors. Results: According to the constructed model, the predictors of CI are axial diffusivity (AD) of the posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB), and mid-posterior corpus callosum (CC). These predictors showed a significant correlation with the volume of white matter hyperintensity; arterial and venous blood flow, pulsatility index, and aqueduct cerebrospinal fluid (CSF) flow; and surface area of the aqueduct, volume of the lateral ventricles and CSF, and gray matter volume. Conclusion: Disturbances in the AD of pvNAWM, CB, and CC, associated with axonal damage, are a predominant factor in the development of CI in CSVD. The relationship between AD predictors and both blood flow and CSF flow indicates a disturbance in their relationship, while their location near the floor of the lateral ventricle and their link with indicators of internal atrophy, CSF volume, and aqueduct CSF flow suggest the importance of transependymal CSF transudation when these regions are damaged.

To search for sensitive predictors of cognitive impairment (CI) and an integrative index of their severity. We assessed CI and diffusion-tensor MRI (DT-MRI) in the regions of interest (ROI) significant for CI in 74 patients (48 women, mean age 60.6±6.9 years) with cerebral small vessel disease (CSVD). The results of DT-MRI were used to construct a predictive model of CI using binary logistic regression and to calculate an integrative index of CI severity. According to the constructed model, the predictors of CI were axial diffusivity (AD) of posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB) and mid-posterior corpus callosum (CC). ROC analysis showed strong model predictive power for CI in cSVD (AUC (95% CI): 0.845 (0.740-0.950)). The threshold value of the AD predictors model for CI in cSVD was 0.53 (sensitivity 84%, specificity 76%). AD predictors of CI showed significant correlations with white matter hyperintensities volume and MoCA scores. The presence of CI as measured by neuropsychological testing and regression equation solution was corresponded to individual AD predictors of patients exceeding the CI model's threshold. Disturbances in the AD of pvNAWM, right middle CB and mid-posterior CC associated with axonal damage are a predominant factor in the development of CI in CSVD. The predictors of CI and the integrative index of CI severity calculated on their basis can potentially be used as a tool for assessing the severity of CI and the effectiveness of treatment, as well as in clarifying the interaction between vascular and degenerative pathology and in developing measures for the prevention of CI in patients with MRI signs of cSVD.

Introduction. Contributing to high disability and mortality, cerebral small vessel disease (cSVD) is a common condition in senior and elderly individuals. Objective: to assess the 5-year survival as well as cognitive and MRI changes in patients with cSVD and cognitive impairment (CI). Materials and methods. A prospective 5-year study included 54 patients (of them 37 women; mean age: 60.51 6.76 years) with cSVD, CIs, and white matter hyperintensities (WMHs; Fazekas 23). Twenty-two subjects were followed up to assess cognitive functions and a type of CI, cSVD MRI features, WMH, white and grey matter, and cerebrospinal fluid (CSF) volume as well as microstructural brain changes and correlate cognitive and MRI parameters at 5 years timepoint after the baseline. Results. Dementia developed in 14% of the subjects and 14% of the subjects died over a 5-year period. The subjects assessed twice had controlled hypertension (HTN). CIs worsened in the domain of executive functions and memory with mixed-type CI worsening. The follow-up showed that the WMH and CSF volume increased while the white matter volume decreased and axial diffusivity increased in the corpus callosum. The CSF volume correlated with the Stroop Test results and delayed memory (r = 0.803 and r = 0.701, respectively) and with white matter atrophy (r = 0.256) while the latter correlated with the axial diffusivity increased in the corpus callosum (r = 0.560). Conclusion. cSVD with advanced WMHs is associated with high mortality and dementia progression. General cognition assessment and MRI scan are not enough sensitive to assess disorder progression over a 5-year period. Stroop Test and Delayed 10-Word Recall Test results and transition to mixed-type CI indicate CI worsening and, therefore, can be used for the follow-up assessment. Cognitive decline in extensive cSVD is mediated by the brain matter atrophy and altered CSF circulation.

The cerebral small vessel disease (cSVD) is one of the main causes of vascular and mixed cognitive impairment (CI), and it is associated, in particular, with brain ageing. An understanding of structural tissue changes in an intact cerebral white matter in cSVD might allow one to develop the sensitive biomarkers for early diagnosis and monitoring of disease progression. Purpose of the study: to evaluate microstructural changes in the corpus callosum (CC) using diffusion MRI (D-MRI) approaches in cSVD patients with different severity of CI and reveal the most sensitive correlations of diffusion metrics with CI. Methods: the study included 166 cSVD patients (51.8% women; 60.4 ± 7.6 years) and 44 healthy volunteers (65.9% women; 59.6 ± 6.8 years). All subjects underwent D-MRI (3T) with signal (diffusion tensor and kurtosis) and biophysical (neurite orientation dispersion and density imaging, NODDI, white matter tract integrity, WMTI, multicompartment spherical mean technique, MC-SMT) modeling in three CC segments as well as a neuropsychological assessment. Results: in cSVD patients, microstructural changes were found in all CC segments already at the subjective CI stage, which was found to worsen into mild CI and dementia. More pronounced changes were observed in the forceps minor. Among the signal models FA, MD, MK, RD, and RK, as well as among the biophysical models, MC-SMT (EMD, ETR) and WMTI (AWF) metrics exhibited the largest area under the curve (>0.85), characterizing the loss of microstructural integrity, the severity of potential demyelination, and the proportion of intra-axonal water, respectively. Conclusion: the study reveals the relevance of advanced D-MRI approaches for the assessment of brain tissue changes in cSVD. The identified diffusion biomarkers could be used for the clarification and observation of CI progression.