Differences in cerebral small vessel disease magnetic resonance imaging depending on cardiovascular risk factors: a retrospective cross-sectional study

Ribera-Zabaco, Marta; Laredo, Carlos; Muñoz-Moreno, Emma; Cabero-Arnold, Andrea; Rosa-Batlle, Irene; Bartolomé-Arenas, Inés; Amaro, Sergio; Chamorro, Ángel; Rudilosso, Salvatore

doi:http://dx.doi.org/10.3390/brainsci15080804

Differences in cerebral small vessel disease magnetic resonance imaging depending on cardiovascular risk factors: a retrospective cross-sectional study

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Citació

Ribera-Zabaco M, Laredo C, Muñoz-Moreno E, Cabero-Arnold A, Rosa-Batlle I, Bartolomé-Arenas I, et al. Differences in cerebral small vessel disease magnetic resonance imaging depending on cardiovascular risk factors: a retrospective cross-sectional study. Brain Sci. 2025;15(8):804. DOI: 10.3390/brainsci15080804

Resum

Background: Vascular risk factors (VRFs) are known to influence cerebral small vessel disease (cSVD) burden and progression. However, their specific impact on the presence and distribution of each cSVD imaging marker (white matter hyperintensity [WMH], perivascular spaces [PVSs], lacunes, and cerebral microbleeds [CMBs]) and their spatial distribution remains unclear. Methods: We conducted a retrospective analysis of 93 patients with lacunar stroke with a standardized investigational magnetic resonance imaging protocol using a 3T scanner. WMH and PVSs were segmented semi-automatically, and lacunes and CMBs were manually segmented. We assessed the univariable associations of four common VRFs (hypertension, hyperlipidemia, diabetes, and smoking) with the load of each cSVD marker. Then, we assessed the independent associations of these VRFs in multivariable regression models adjusted for age and sex. Spatial lesion patterns were explored with regional volumetric comparisons using Pearson’s coefficient analysis, which was adjusted for multiple comparisons, and by visually examining heatmap lesion distributions. Results: Hypertension was the VRF that exhibited stronger associations with the cSVD markers in the univariable analysis. In the multivariable analysis, only lacunes (p = 0.009) and PVSs in the basal ganglia (p = 0.014) and white matter (p = 0.016) were still associated with hypertension. In the regional analysis, hypertension showed a higher WMH load in deep structures and white matter, particularly in the posterior periventricular regions. In patients with hyperlipidemia, WMH was preferentially found in hippocampal regions. Conclusions: Hypertension was confirmed to be the VRF with the most impact on cSVD load, especially for lacunes and PVSs, while the lesion topography was variable for each VRF. These findings shed light on the complexity of cSVD expression in relation to factors detrimental to vascular health.