Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2026 Jan 28;51(1):97-108. doi: 10.11817/j.issn.1672-7347.2026.250596.
ABSTRACT
OBJECTIVES: The mechanism of abnormal eye movements in patients with cerebral small vessel disease (CSVD) remains unclear. This study aims to explore the potential link between eye movement in CSVD patients and the severity and distribution of white matter hyperintensities (WMH), and to evaluate the possibility of using eye movement assessment as a tool for specific diagnosis.
METHODS: This retrospective cross-sectional study was conducted at Xiangya Hospital, Central South University between September 7th, 2022 and October 27th, 2023, enrolling a total of 161 patients with CSVD. Demographic characteristics, past medical history, medication history, and imaging data were collected. The Montreal Cognitive Assessment (MoCA) was used to evaluate patients' cognitive function, and the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD) were used to assess patients' anxiety and depressive symptoms. All participants completed the EyeKnow Intelligent Eye Movement Analysis System within one week of enrollment, with data recorded on the following eye movement paradigms: saccade, smooth pursuit, fixation, and antisaccade. WMH were scored using both the Age-Related White Matter Change (ARWMC) scale and the Fazekas grading system. Based on the scores, patients were categorized into three severity groups (mild, moderate, severe). The Kruskal-Wallis rank sum test was used to analyze intergroup differences, while Spearman correlation analysis and multiple linear regression were used to explore the relationship between eye movement characteristics and WMH. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the ability of eye movement characteristics to discriminate between patients with and without WMH in the five brain regions: frontal lobe, temporal lobe, parietal-occipital lobe, infratentorial region, and basal ganglia region. A weighted random forest model was developed to assess the performance of eye movement characteristics in predicting WMH severity at different locations.
RESULTS: This study enrolled a total of 161 patients with CSVD. Baseline data were collected for all participants. According to the total ARWMC scores, patients were divided into a mild (0 to 10 points), a moderate (11 to 20 points), and a severe (21 to 30 points) WMH groups. The mild WMH group included 100 patients [66 males and 34 females, age (61.40±9.45) years]. The moderate WMH group included 46 patients [32 males and 14 females, age (63.72±8.77) years]. And the severe WMH group included 15 patients [12 males and 3 females, age (63.47±10.40) years]. Significant differences were observed among the 3 groups in MoCA scores (P=0.008), severity of cerebral microbleeds (CMB) (P<0.001), severity of basal ganglia perivascular spaces (BG-PVS) (P<0.001), and global cortical atrophy (GCA) grading system scores (P=0.003). Analysis of intergroup differences in eye movement characteristics revealed that with increasing WMH severity, the fastest saccade reaction time increased (P=0.008), the smooth pursuit deviation (P=0.013) and the number of fixation shifts (>2°) (P=0.025) decreased. In post-hoc pairwise comparisons, there were no significant differences in any eye movement characteristics between the moderate and severe WMH group (all P>0.05). Spearman correlation analysis demonstrated a strong positive correlation between the total Fazekas and total ARWMC scores (r=0.867, P<0.01), confirming their concordance for rating WMH severity. Additionally, MoCA scores were significantly negatively correlated with both the total Fazekas scores (r=-0.302, P<0.01) and the total ARWMC scores (r=-0.245, P<0.01). Multiple linear regression analysis based on the total ARWMC scores revealed that after adjusting for multicollinearity, oculomotor features including smooth pursuit initiation time (β=-0.001, P=0.009), smooth pursuit deviation (β=-1.212, P=0.001), number of fixation shifts (>2°) (β=-0.102, P=0.011), and mean reaction time of antisaccade (β=0.016, P=0.018) remained statistically significant predictors of cognitive function. After adjusting for gender, age, years of education, MoCA, HAMA, HAMD scores, and the presence of other imaging markers, the associations of smooth pursuit initiation time (β<0.001, P=0.010), smooth pursuit deviation (β=-1.066, P=0.002), and mean reaction time of antisaccade (β=0.013, P=0.034) with the outcome variable remained statistically significant. In the distribution of WMH locations, ROC curve analysis was conducted based on all eye movement characteristics to discriminate the presence of WMH in the whole brain, frontal lobe, temporal lobe, parietal-occipital lobe, and infratentorial region, with AUC values of 0.933, 0.928, 0.758, 0.784, and 0.881, respectively. For the basal ganglia region, binary logistic regression analysis showed no significant association, and therefore ROC curve analysis was not applicable. Using a weighted random forest method, the severity of WMH at different locations was further classified. After adjusting for gender, age, years of education, MoCA, HAMA, HAMD scores, and the presence of other imaging markers, the model's classification accuracy improved to 85.71% for the frontal lobe, 81.63% for the infratentorial region, and 75.51% for the parietal-occipital lobe.
CONCLUSIONS: The eye movement performance of CSVD patients worsens with the increasing severity of WMH, especially in the frontal lobe and infratentorial region. Cognitive function exerts an influence on eye movement that appears largely independent of imaging changes.
PMID:42032963 | DOI:10.11817/j.issn.1672-7347.2026.250596