The Combination of Retinal Neurovascular Unit Changes With Carotid Artery Stenosis Enhances the Prediction of Ischemic Stroke.

Purpose: We aimed to analyze retinal neurovascular unit (RNVU) alterations and function via optical coherence tomography angiography (OCTA) and full-field electroretinography (ERG) in patients with ischemic stroke (IS).

Methods: OCTA was used to measure RNVU changes in 229 participants (101 with IS and 128 healthy controls). The RETeval device was used to record full-field electroretinograms (FERGs) in 40 participants (14 with IS and 26 healthy controls). Logistic regression models for IS were constructed. Receiver operating characteristic (ROS) curves were constructed to assess the predictive value of various models for IS.

Results: Patients with ipsilateral internal carotid artery stenosis (ICAS) had a greater occurrence of IS. A decrease in the vascular density (VD) of the parafovea, FD-300, and nasal optic disc; a decrease in the thickness of the retinal nerve fiber layer (RNFL) around the nasal optic disc; and an increase in the acircularity index (AI) were observed in patients with IS (P < 0.05). An increase in the AI was identified as a risk factor for IS, whereas the other factors were found to be protective factors. The IS group presented a delayed a-wave implicit time and decreased b-wave amplitudes at the scotopic point. By incorporating traditional risk factors, the degree of ipsilateral ICAS, and OCTA parameters, a high predictive value for IS was achieved (area under the curve [AUC] = 0.933).

Conclusions: Patients with IS without visible fundus lesions presented changes in the RNVU, characterized by reductions in retinal VD and RNFL thickness, alongside dysfunction of photoreceptor cells and bipolar cells. The combination of RNVU changes with traditional risk factors can enhance the prediction of IS, which provides valuable guidance for monitoring this disease.

Translational relevance: This study demonstrated that the combination of OCTA parameters, the degree of ipsilateral ICAS, and traditional risk factors could can enhance the prediction of IS. These findings provide valuable guidance for monitoring IS by assessing RNVUs.