We aimed to investigate alterations in functional brain networks and assess the relationship between functional impairment and topological network changes in cerebral small vessel disease (CSVD) patients with and without cerebral microbleeds (CMBs). We constructed individual whole‐brain, region of interest (ROI) level functional connectivity (FC) networks for 24 CSVD patients with CMBs (CSVD‐c), 42 CSVD patients without CMBs (CSVD‐n), and 36 healthy controls (HCs). Then, we used graph theory analysis to investigate the global and nodal topological disruptions between groups and relate network topological alterations to clinical parameters. We found that both the CSVD and control groups showed efficient small‐world organization in FC networks. However, compared to CSVD‐n patients and controls, CSVD‐c patients exhibited a significantly decreased clustering coefficient, global efficiency, and local efficiency and an increased shortest path length, indicating a disrupted balance between local specialization and global integration in FC networks. Although both the CSVD and control groups showed highly similar hub distributions, the CSVD‐c group exhibited significantly altered nodal betweenness centrality (BC), mainly distributed in the default mode network (DMN), attention, and visual functional areas. There were almost no global or regional alterations between CSVD‐n patients and controls. Furthermore, the altered nodal BC of the right anterior/posterior cingulate gyrus and left cuneus were significantly correlated with cognitive parameters in CSVD patients. These results suggest that CSVD patients with and without CMBs had segregated disruptions in the topological organization of the intrinsic functional brain network. This study advances our current understanding of the pathophysiological mechanisms underlying CSVD.

Quantitative susceptibility mapping (QSM) can study the susceptibility values of brain tissue which allows for noninvasive examination of local brain iron levels in both normal and pathological conditions. Our study compares brain iron deposition in gray matter (GM) nuclei between cerebral small vessel disease (CSVD) patients and healthy controls (HCs), exploring factors that affect iron deposition and cognitive function. A total of 321 subjects were enrolled in this study. All subjects had cognitive examination including the Stroop color word test (SCWT) and MRI including multiecho gradient echo (mGRE) sequence. The patients with CSVD were divided into mild to moderate group (CSVD-M, total CSVD score ≤ 1) and severe group (CSVD-S, total CSVD score > 1). Morphology-enabled dipole inversion with an automated uniform cerebrospinal fluid zero reference algorithm (MEDI + 0) was used to generate brain QSM maps from mGRE data. Deep gray regional susceptibility values and cognitive function were compared among three groups (CSVD-S, CSVD-M, and HC) using multiple linear regression analysis and mediation effect analysis. There were significant differences in the SCWT scores and mean susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN) among the three groups (P < 0.05, FDR correction). Age had a significant positive impact on the susceptibility values of GP (p = 0.018), Put (p < 0.001), and CN (p < 0.001). A history of diabetes had a significant positive influence on the susceptibility values of Put (p = 0.011) and CN (p < 0.001). A smoking history had a significant positive association with the susceptibility values of CN (p = 0.019). Mediation effect analysis demonstrated that iron deposition in the neostriatum partially mediated the relationship between hypertension and cognitive function. Age, diabetes, and smoking may increase iron deposition in the basal ganglia, associated with cognitive decline. The mean susceptibility values of the neostriatum played a mediating role in the association between hypertension and cognitive scores. Age, diabetes, and smoking are associated with increased iron deposition in the basal ganglia and also linked to cognitive decline. This can help with understanding CSVD and its prevention and treatment.

Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore white matter (WM) microstructural alterations. Cerebral small vessel disease (CSVD) may be accompanied by extensive WM microstructural deterioration, while cerebral microbleeds (CMBs) are an important factor affecting CSVD. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups. Compared with the CSVD-n and control groups, the CSVD-c group showed a significant FA decrease and AD, RD and MD increases mainly in the cognitive and sensorimotor-related WM tracts. There was no significant difference in any diffusion metric between the CSVD-n and control groups. Furthermore, the widespread regional diffusion alterations among groups were significantly correlated with cognitive parameters in both the CSVD-c and CSVD-n groups. Notably, we applied the multiple kernel learning technique in multivariate pattern analysis to combine multiregion and multiparameter diffusion features, yielding an average accuracy >77 % for three binary classifications, which showed a considerable improvement over the single modality approach. We only grouped the study according to the presence or absence of CMBs. CSVD patients with CMBs have extensive WM microstructural deterioration. Combining DTI-derived diffusivity and anisotropy metrics can provide complementary information for assessing WM alterations associated with cognitive dysfunction and serve as a potential discriminative pattern to detect CSVD at the individual level.

To reveal the network-level structural disruptions associated with cognitive dysfunctions in different cerebral small vessel disease (CSVD) burdens, we used probabilistic diffusion tractography and graph theory to investigate the brain network topology in 67 patients with a severe CSVD burden (CSVD-s), 133 patients with a mild CSVD burden (CSVD-m) and 89 healthy controls. We used one-way analysis of covariance to assess the altered topological measures between groups, and then evaluated their Pearson correlation with cognitive parameters. Both the CSVD and control groups showed efficient small-world organization in white matter (WM) networks. However, compared with CSVD-m patients and controls, CSVD-s patients exhibited significantly decreased local efficiency, with partially reorganized hub distributions. For regional topology, CSVD-s patients showed significantly decreased nodal efficiency in the bilateral anterior cingulate gyrus, caudate nucleus, right opercular inferior frontal gyrus (IFGoperc), supplementary motor area (SMA), insula and left orbital superior frontal gyrus and angular gyrus. Intriguingly, global/local efficiency and nodal efficiency of the bilateral caudate nucleus, right IFGoperc, SMA and left angular gyrus showed significant correlations with cognitive parameters in the CSVD-s group, while only the left pallidum showed significant correlations with cognitive metrics in the CSVD-m group. In conclusion, the decreased local specialization of brain structural networks in patients with different CSVD burdens provides novel insights into understanding the brain structural alterations in relation to CSVD severity. Cognitive correlations with brain structural network efficiency suggest their potential use as neuroimaging biomarkers to assess the severity of CSVD.

Aims: Emerging evidence suggests that cerebral small vessel disease (CSVD) pathology changes brain structural connectivity (SC) and functional connectivity (FC) networks. Although network‐level SC and FC are closely coupled in the healthy population, how SC‐FC coupling correlates with neurocognitive outcomes in patients with different CSVD burdens remains largely unknown.Methods: Using multimodal MRI, we reconstructed whole‐brain SC and FC networks for 54 patients with severe CSVD burden (CSVD‐s), 106 patients with mild CSVD burden (CSVD‐m), and 79 healthy controls. We then investigated the aberrant SC‐FC coupling and functional network topology in CSVD and their correlations with cognitive dysfunction.Results: Compared with controls, the CSVD‐m patients showed no significant change in any SC‐FC coupling, but the CSVD‐s patients exhibited significantly decreased whole‐brain (p = 0.014), auditory/motor (p = 0.033), and limbic modular (p = 0.011) SC‐FC coupling. For functional network topology, despite no change in global efficiency, CSVD‐s patients exhibited significantly reduced nodal efficiency of the bilateral amygdala (p = 0.024 and 0.035) and heschl gyrus (p = 0.001 and 0.005). Notably, for the CSVD‐s patients, whole‐brain SC‐FC coupling showed a significantly positive correlation with MoCA (r = 0.327, p = 0.020) and SDMT (r = 0.373, p = 0.008) scores, limbic/subcortical modular SC‐FC coupling showed a negative correlation (r = −0.316, p = 0.025) with SCWT score, and global/local efficiency (r = 0.367, p = 0.009 and r = 0.353, p = 0.012) showed a positive correlation with AVLT score. For the CSVD‐m group, whole‐brain and auditory/motor modular SC‐FC couplings showed significantly positive correlations with SCWT (r = 0.217, p = 0.028 and r = 0.219, p = 0.027) and TMT (r = 0.324, p = 0.001 and r = 0.245, p = 0.013) scores, and global/local efficiency showed positive correlations with AVLT (r = 0.230, p = 0.020 and r = 0.248, p = 0.012) and SDMT (r = 0.263, p = 0.008 and r = 0.263, p = 0.007) scores.Conclusion: Our findings demonstrated that decreased whole‐brain and module‐dependent SC‐FC coupling associated with reduced functional efficiency might underlie more severe burden and worse cognitive decline in CSVD. SC‐FC coupling might serve as a more sensitive neuroimaging biomarker of CSVD burden and provided new insights into the pathophysiologic mechanisms of clinical development of CSVD.

Neuroimaging studies have demonstrated extensive brain functional alterations in cognitive and motor functional areas in Type 2 diabetes mellitus (T2DM) with diabetic peripheral neuropathy (DPN), suggesting potential alterations in large‐scale brain networks related to DPN and associated cognition and motor dysfunction. In this study, using resting‐state functional connectivity (FC) and graph theory computational approaches, we investigated the topological disruptions of brain functional networks in 28 DPN, 43 T2DM without DPN (NDPN), and 32 healthy controls (HCs) and examined the correlations between altered network topological metrics and cognitive/motor function parameters in T2DM. For global topology, NDPN exhibited a significantly decreased shortest path length compared with HCs, suggesting increased efficient global integration. For regional topology, DPN and NDPN had separated topological reorganization of functional hubs compared with HCs. In addition, DPN showed significantly decreased nodal efficiency (E_nodal), mainly in the bilateral superior occipital gyrus (SOG), right cuneus, middle temporal gyrus (MTG), and left inferior parietal gyrus (IPL), compared with NDPN, whereas NDPN showed significantly increased E_nodal compared with HCs. Intriguingly, in T2DM patients, the E_nodal of the right SOG was significantly negatively correlated with Toronto Clinical Scoring System scores, while the E_nodal of the right postcentral gyrus (PoCG) and MTG were significantly positively correlated with Montreal Cognitive Assessment scores. Conclusively, DPN and NDPN patients had segregated disruptions in the brain functional network, which were related to cognition and motion dysfunctions. Our findings provide a theoretical basis for understanding the neurophysiological mechanism of DPN and its effective prevention and treatment in T2DM.