Correlation between Cerebral Small Vessel Disease and Brain Artery Remodeling and Its Hemodynamic Characteristics: An Investigation Based on 4D Flow MRI.

RATIONALE AND OBJECTIVES: The cerebrovascular system features complex anatomical and functional connectivity. Brain artery remodeling (BAR) and cerebral small vessel disease (CSVD) are two distinct phenotypes of cerebrovascular injury, yet they are closely intertwined at the pathophysiological level. However, existing studies have failed to integrate the analysis of morphological features of vascular remodeling and hemodynamic alterations, leading to insufficient objective evidence supporting the causal and correlational link between the two pathologies. Using four-dimensional flow magnetic resonance imaging (4D Flow MRI), this study aimed to characterize BAR-related ischemic changes and their corresponding hemodynamic profiles in CSVD, and to explore the hemodynamic association between BAR and neuroimaging markers of CSVD.

MATERIALS AND METHODS: Consecutive subjects admitted between December 2023 and December 2024 were prospectively enrolled in this study. All subjects underwent standardized neuroimaging examinations to assess the four core imaging markers of CSVD: lacunar infarcts (LIs), cerebral microbleeds (CMBs), enlarged perivascular spaces (EPVS), and white matter hyperintensities (WMHs). Hemodynamic parameters were quantitatively measured using 4D Flow MRI, and vascular diameters of intracranial major arteries were obtained to calculate the BAR score. Statistical analyses were performed to investigate the associations among hemodynamic indices, BAR score, and the presence and severity of CSVD.

RESULTS: A total of 154 consecutive subjects were prospectively enrolled and included in the final analysis of this study. According to the total CSVD burden score, subjects were stratified into the non-CSVD group (n = 42), mild CSVD group (n = 74), and severe CSVD group (n = 38). Significant differences were observed in BAR severity, clinical features, and hemodynamic profiles across groups. Logistic regression identified key predictors: age, abnormal hemodynamic indices, and BAR score for both CSVD diagnosis and severity; hyperlipidemia for CSVD diagnosis; and hypertension for CSVD severity. The comprehensive diagnostic model achieved excellent Area Under the Curve values: 0.912 for CSVD presence and 0.876 for CSVD severity. Incorporation of the BAR score significantly improved diagnostic accuracy and classification performance.

CONCLUSION: This cross-sectional study demonstrated that patients with CSVD, especially those with severe CSVD, presented with neuroimaging features of intracranial arterial dilated remodeling. 4D Flow MRI enables reliable identification of the abnormal hemodynamic characteristics associated with CSVD, which provides a novel perspective for elucidating the pathophysiological mechanisms underlying CSVD.