Retinal Structural and Microvascular Alterations in Different Acute Ischemic Stroke Subtypes - Ying Zhang; Ce Shi; Yihong Chen; Weicheng Wang; Shenghai Huang; Zhao Han; Xianda Lin; Fan Lu; Meixiao Shen (Journal of Ophthalmology)
Introduction. Retinal structural and microvascular damages reflect damage to cerebral microvasculature and neurons. We aimed to investigate neovascular unit abnormalities among patients with large-artery atherosclerosis (LAA) or small-vessel occlusion (SAA) and control subjects. Methods. Twenty-eight LAA patients, forty-one SAA patients, and sixty-five age- and gender-matched controls were recruited. Based on optical coherence tomography angiography (OCTA), retinal capillary vessel density was assessed in the general and local sectors, and the thickness of individual retinal layer was extracted from retinal structural images. The differences between structural and microvascular were analyzed. Results. The superior peripapillary retinal nerve fiber layer (pRNFL) thickness was significantly different among the three groups, and the LAA group had the thinnest thickness. Compared to the control group, the deep retinal capillary vessel density in other two stroke subgroups were significantly reduced in all regions except in the inferior region (P < 0.05), and the fractal dimension in C2 and C4 regions of deep retina was significantly lower in the LAA group (P < 0.05). Discussion. Compared with superficial microvascular network, deep microvascular network is more sensitive to ischemic stroke. In addition, we have demonstrated quadrant-specific pRNFL abnormalities in LAA and SAA patients. Superior quadrant pRNFL thickness differences between stroke subgroups may suggest that changes in retinal nerve fiber layer are more sensitive to subtype identification than changes in retinal microvascular structure. All in all, the alteration in retinal structural and microvascular may further elucidate the role of the neovascular unit in ischemic stroke, suggesting that the combination of these two indicators could be used for subtype identification to guide prognosis and establish a risk prediction model.