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Retinal Structural and Microvascular Alterations in Different Acute Ischemic Stroke Subtypes.

Ying Zhang¹, Ce Shi¹, Yihong Chen¹

¹School of Ophthalmology and Optometry, Wenzhou Medical College, Wenzhou, Zhejiang, China.

Journal of Ophthalmology

|January 25, 2021

Summary

Retinal nerve fiber layer thickness and deep capillary vessel density differ between stroke subtypes and controls. These retinal changes may help identify stroke types and predict outcomes.

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Area of Science:

Ophthalmology
Neurology
Vascular Biology

Background:

Retinal structural and microvascular changes can indicate cerebral damage.
Investigating neovascular unit abnormalities is crucial for understanding stroke.
Large-artery atherosclerosis (LAA) and small-vessel occlusion (SAA) are common stroke types.

Purpose of the Study:

To investigate neovascular unit abnormalities in patients with LAA or SAA compared to controls.
To assess retinal structural and microvascular differences across stroke subtypes.
To explore the potential of retinal indicators for stroke subtype identification.

Main Methods:

Optical coherence tomography angiography (OCTA) was used to assess retinal capillary vessel density.
Retinal structural images were analyzed to extract the thickness of individual retinal layers.
Retinal nerve fiber layer (pRNFL) thickness and capillary vessel density were compared among LAA patients, SAA patients, and controls.

Main Results:

Superior peripapillary retinal nerve fiber layer (pRNFL) thickness was significantly thinner in the LAA group.
Deep retinal capillary vessel density was reduced in LAA and SAA patients compared to controls, except in the inferior region.
Lower fractal dimensions in deep retinal regions (C2, C4) were observed in the LAA group.

Conclusions:

The deep microvascular network is more sensitive to ischemic stroke than the superficial network.
Quadrant-specific pRNFL abnormalities were identified in LAA and SAA patients.
Combining retinal structural and microvascular indicators may aid in stroke subtype identification, prognosis, and risk prediction.