Stroke Side Identification in the Brain by Retinal Image Analysis

Abstract Purpose To establish a prediction model for stroke side identification.Methods A total of 168 patients (89 left-sided stroke patients and 79 right-sided stroke patients) were recruited from the Shenzhen Traditional Chinese Medicine Hospital in the study. Retinal characteristics were analyzed using an automated retinal image analysis (ARIA) system. Multivariable logistic regression was used to identify and develop predictive models. Results Each unit increase in the right eye bifurcation coefficient of arterioles increased the risk of right-side stroke by 7.523 times (95% CI, 1.823-31.044). Additionally, an elevated bifurcation coefficient of venules in the right eye also increased the risk of stroke in the right side of the brain, with an odds ratio (OR) of 7.377 (95% CI, 1.771-30.724). A complex retinal composite score was also associated with a higher risk of right-side stroke (OR, 4.955; 95% CI, 3.061-8.022). Conclusion This study demonstrated that retinal image analysis can provide useful information for stroke side identification and the specific retinal characteristics may help in predicting stroke occurrence.