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.

Objective. To assess the microstructural integrity of the corpus callosum in patients with cerebral small vessel disease (cSVD) using signal and biophysical diffusion MRI models and to identify the most sensitive markers of disease progression. Material and methods. Diffusion MRI (3 Tesla) was performed in 166 patients (51.8% women; mean age 60.4±7.6) with cSVD and cognitive impairment of varying severity and in 44 healthy volunteers (65.9% women; mean age 59.6±6.8), followed by calculation of signal (diffusion tensor and diffusion kurtosis) and biophysical (WMTI, NODDI, MC-SMT) models, from which profiles of three corpus callosum segments were constructed. Results. The best results were obtained for metrics in the forceps minor and body of the corpus callosum. Among the metrics of the signal models in the forceps minor, fraction anisotropy (FA) and mean diffusion (MD), which characterize the overall loss of microstructural integrity and increase in extra-axonal water, as well as indirect markers of demyelination when considering transverse diffusion parameters (radial diffusion and radial kurtosis), had the larger area under the curve according to the ROC analysis. Among the metrics of the biophysical models in the forceps minor, a larger area under the curve was found in the MC-SMT model for extra-axonal transverse diffusion (ETR), mean diffusion (EMD), and intra-axonal water fraction (INTRA), and in the WMTI model for intra-axonal water fraction (AWF). ETR had high inverse correlations with INTRA and AWF, while INTRA and AWF had high direct intercorrelations. Conclusion. Metrics of signaling (FA, MD, RD, RK) and biophysical patterns (ETR, EMD, INTRA, AWF) in the forceps minor and the corpus callosum body can be considered as indicators of cSVD progression. They indicate disease progression, mainly by an increase in extra-axonal water with the development of demyelination and tissue degeneration in the corpus callosum.

Introduction. Cerebral small vessel disease (CSVD) as well as the Alzheimer's disease (AD) and their comorbidities are the most common causes of cognitive impairments (CIs). Objective: to evaluate the predictive power of the biochemical neurodegeneration markers in patients with CSVD and AD. Materials and methods. We assessed the following neurodegeneration markers in 68 patients with CSVD (61.0 8.6 years; 60.3% males), 17 patients with AD (65.2 8.3 years; 35.3% males), and 26 healthy volunteers (59.9 6.7 years; 38.5% males): neuron-specific enolase (NSE), glial fibrillary acid protein (GFAP), neurofilament light polypeptide (NEFL) in blood (for all patients) and in cerebrospinal fluid (CSF; in patients with CSVD and AD). We assessed the predictive power of those markers with ROC analysis. Results. As compared to the control group, serum GFAP in patients with CSVD showed its predictive power at 0.155 ng/ml (sensitivity 74%; specificity 70%). Serum NEFL 0.0185 ng/ml (sensitivity 82%; specificity 96%) and NSE 4.95 g/ml (sensitivity 77%; specificity 71%) showed their predictive power in patients with AD. CSF GFAP 1.03 ng/ml (sensitivity 84%; specificity 88%), CSF NSE 19.10 g/ml (sensitivity 88%; specificity 91%), serum NEFL 0.021 ng/ml (sensitivity 71%; specificity 76%), serum NSE /CSF NSE ratio 0.273 ng/ml (sensitivity 87%; specificity 88%) help differentiate CSVD from AD. Conclusions. We found that serum GFAP can be a useful diagnostic marker in patients with CSVD, while serum NEFL and serum NSE can help identify the AD. In addition, CSF GFAP and CSF NSE as well as serum NEFL and serum NSE/CSF NSE can help differentiate CSVD from AD. We can use those markers in clinical and research practice to identify the vascular and neurodegenerative causes of CIs and their comorbidities, which is of a great importance in developing specific treatment and predicting the course of the disease.

Objective. To assess the impaired ambulation and the fall risk in patients with cerebral microangiopathy (CMA), and their association with the microstructural integrity of the tracts involved in walking. Material and methods. One hundred twenty-four patients with CMA (STRIVE, 2013) and hyperintensity of white matter at the Fazekas stage 2—3 (mean age 62.2±7.9), and 30 healthy volunteers of the control group (mean age 59.8±6.4) underwent a comprehensive assessment of walking using the Tinetti tests, the 6-meter walk test, and the clinical scale of the impaired ambulation severity. Based on the diffusion MRI data, 80 patients with CMA and 21 healthy volunteers of the control group were assessed for fractional anisotropy (FA) in the frontopontine, corticoreticulospinal, and pontocerebellar tracts using a segmentation method. Results. 68.5% of CMA patients showed impaired ambulation, and 41.9% had a moderate and high fall risk. FA, reflecting overall microstructural integrity, in the frontopontine and corticoreticulospinal tracts correlated with the results of the Tinetti test («balance» subscale and total score) and consistently decreased as the severity of impaired ambulation and the fall risk increased. For the most significant sections of the tracts (60—80, 80—95), ROC analysis obtained threshold FA values associated with the development of mild impaired ambulation and moderate fall risk, with high sensitivity and specificity (AUC>0.75). Conclusion. Impaired ambulation and associated fall risk are common in patients with CMA. Microstructural damage (assessed by FA) of the frontopontine and corticoreticulospinal tracts, mainly at the level of subcortical and deep white matter, is crucial for the development of impaired ambulation and fall risk. The obtained FA threshold values of these tracts can be used as objective markers to identify patients at high risk of impaired ambulation and fall risk in the early stages, which is essential for timely prevention.

Background/Objectives: Cerebral small vessel disease (SVD) is a heterogeneous condition in which similar conventional MRI findings may be associated with different clinical manifestations and pathogenetic mechanisms. Previously, hierarchical clustering of structural MRI features in patients with severe white matter hyperintensities (Fazekas 3) identified two MRI phenotypes, designated MRI Type 1 and MRI Type 2. Diffusion MRI (dMRI) may provide additional information about the microstructural differences between these phenotypes. To compare white matter microstructure between MRI Type 1 and MRI Type 2 of sporadic age-related SVD using signal-based and biophysical dMRI models. Methods: This cross-sectional study included 75 patients with SVD and 36 age- and sex-matched healthy controls. Among the patients with SVD, 43 had MRI Type 1 and 32 had MRI Type 2. All participants underwent structural and multi-shell dMRI on a 3 Tesla MRI scanner. Diffusion metrics were derived using multiple models: Diffusion Tensor Imaging (DTI), Diffusion Kurtosis Imaging (DKI), Neurite Orientation Dispersion and Density Imaging (NODDI), White Matter Tract Integrity (WMTI), and the Multi-compartment Spherical Mean Technique (MC-SMT). Tract-profile analysis was performed in three corpus callosum segments: the forceps major, forceps minor, and body. Group differences were assessed using age- and sex-adjusted general linear models with correction for multiple comparisons. The combined discriminative value of dMRI metrics was evaluated using regularized Elastic Net logistic regression with repeated nested five-fold cross-validation. Results: After adjustment for age and sex, the overall group effect remained significant for 45 of 48 global dMRI measures following Benjamini–Hochberg correction. Compared with MRI Type 2, MRI Type 1 showed lower fractional anisotropy (FA), neurite density index (NDI), intra-axonal volume fraction (INTRA), axonal water fraction (AWF), mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK), and higher mean diffusivity (MD), radial diffusivity (RD), extra-axonal mean diffusivity (EXTRA_MD), extra-axonal transverse diffusivity (EXTRA_TRANS), and extra-axonal radial diffusivity (radEAD). These differences were generally most pronounced in the body of the corpus callosum. In the segmental analysis, 131 of 144 values showed a significant overall group effect after correction, and 108 demonstrated significant differences between MRI Type 1 and MRI Type 2. The largest effects were observed in the 60–80% interval of the corpus callosum body, particularly for AWF, MK, INTRA, EXTRA_TRANS, RK, FA, RD, radEAD, and MD. An Elastic Net model combining age, sex, and 48 global dMRI measures discriminated MRI Type 1 from MRI Type 2 with an internally validated area under the curve of 0.866 (95% CI, 0.762–0.953), accuracy of 86.7%, sensitivity of 75.0%, and specificity of 95.3%. Ten dMRI features showed a selection frequency of at least 70% across repeated model construction. Conclusions: MRI Type 1 is characterized by more severe and spatially extensive corpus callosum microstructural abnormalities than MRI Type 2, despite broadly similar vascular risk-factor profiles. The findings support the heterogeneity of sporadic age-related SVD and indicate that combined signal-based and biophysical dMRI metrics may improve MRI phenotyping. The observed associations should be interpreted as indirect markers of tissue microstructure and require confirmation in larger, independent, and longitudinal cohorts.

Age-dependent cerebral microangiopathy (also known as cerebral small vessel disease) is a common heterogeneous condition that ranks high as a cause of disability and mortality of elderly patients due to strokes and intracerebral hemorrhages, vascular cognitive disorders, walking disorders, and the induction of neurodegeneration. In this review, we 1) describe the achievements of neuroimaging in the diagnosis of the age-dependent cerebral microangiopathy forms and the standardization of clinical and experimental studies; 2) analyze the possibilities and prospects of using a lifetime MRI assessment of the brain microstructure and pathophysiological mechanisms of its damage associated with neurovascular unit dysfunction; 3) provide evidence of pathomorphosis of the disease, due to, among other things, the control of vascular risk factors, and indicate the need to search for new risk factors with the determination of individual susceptibility to them; 4) indicate the need to use experimental models of CMA that consider its pathomorphosis, and pay attention to the prospects of endothelial dysfunction models; 5) assess the prospects for the development of pathogenetic treatment in terms of finding molecular targets using omics technologies. The complexity of the condition and the limited approaches to its prevention indicate the need for consortium discussion and collaboration of various specialists in the field of neuroscience for advancements in the management of this disease.