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.

Aims: We aimed to specify relationships among cerebral small vessel disease (CSVD) burden, cognitive dysfunction, and brain structure–function coupling changes. Methods: A total of 108 patients with mild CSVD burden (CSVD‐m), 53 patients with severe CSVD burden (CSVD‐s), and 76 healthy controls (HC) were included in this study. The ratio of regional homogeneity (ReHo) or amplitude of low‐frequency fluctuation (ALFF) to gray matter volume (GMV) was calculated as an indicator of voxel‐wise structure–function coupling. Results: Significantly decreased or increased ReHo–GMV and ALFF–GMV coupling values in patients with severe CSVD burden were primarily found in several brain regions, and the disrupted structure–function coupling in the right putamen mediated the relationship between CSVD burden and cognitive dysfunction. Conclusions: Brain structure–function coupling characterized by ReHo–GMV and ALFF–GMV mediated the cognitive dysfunction caused by CSVD and was an innovative and effective brain imaging indicator for exploring the association between CSVD burden and cognitive dysfunction.

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that significantly impacts cognitive health. Although the vascular complications of T2DM have been extensively studied, research on brain iron deposition in T2DM remains scarce, and few studies have directly linked iron accumulation in cognition‐related subcortical nuclei to cognitive dysfunction. This study aims to evaluate brain iron deposition using quantitative susceptibility mapping (QSM) and identify key subcortical nuclei associated with T2DM‐related cognitive decline. A total of 224 participants were recruited, including 112 T2DM patients and 112 healthy controls. QSM was used to assess iron deposition in subcortical nuclei. Structural equation modeling was employed to construct interaction models between metabolic changes, susceptibility values, and cognitive function. Additionally, polynomial regression analysis was performed to evaluate the association between glycemic variability and the QSM values of subcortical nuclei. Our findings confirmed that T2DM patients exhibited pronounced iron deposition in the caudate and putamen compared to healthy controls. Correlation analyses showed that higher QSM values in the anterior putamen, posterior putamen, and posterior caudate were associated with slower processing speed (SDMT), reduced memory performance (AVLT) and poorer executive function (TMT, SCWT), indicating that greater iron accumulation in these nuclei is associated with poorer cognitive performance. In our SEM, metabolic dysregulation was significantly associated with higher subcortical susceptibility (β = 0.224, p = 0.010). The model further demonstrated that susceptibility values partially mediated the effect of metabolic factors on cognition (indirect effect β = −0.056, p = 0.018) and that the overall impact of metabolic dysregulation on cognition remained significant (β = −0.142, p = 0.037). Polynomial regression found that HbA1c was the strongest predictor of anterior putamen susceptibility, and a similar pattern was observed in the posterior caudate. The study demonstrates that the role of brain iron deposition in T2DM‐related cognitive dysfunction. These findings reveal an important underlying mechanism of T2DM‐induced cognitive impairment and provide evidence for early intervention strategies to mitigate cognitive decline in T2DM patients.