Clinical Features Evaluation of Myopic Fundus tessellation from OCTA and MfERG.

Yanyan Zhang, Yan Zhong, Wei Mao, Zhe Zhang, Yusheng Zhou, Hu Li, Jianing Ying, Quanyong Yi
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Abstract

Purpose: To evaluate the differences in fundus tessellation among various severities using multifocal visual electrophysiology (MfERG) and optical coherence tomography angiography (OCTA) for clinical grading and treatment.

Methods: This study included 52 patients totaling 87 eyes. The Early Treatment Diabetic Retinopathy Study (ETDRS) grid division method was utilized to assess Grade of fundus tessellation. Data obtained via OCTA and ImageJ software included macular foveal thickness (MT), subfoveal choroidal thickness (SFCT), superficial retinal capillary layer vascular density (SVD), deep retinal capillary layer vascular density (DVD), and choroidal blood capillary layer blood flow density (CFD). Multifocal visual electrophysiology equipment provided latency and amplitude of N1 and P1 waves. Differences and changes among the four Grade of fundus tessellation grading were compared, and ROC curve analysis was performed to identify the optimal choroidal thickness indicators for predicting the grading of fundus tessellation.

Results: SFCT tends to decrease as the grade of fundus tessellation increases. and the amplitudes of N1 and P1 waves in multifocal electroretinography reduce, with an elongation in their latency periods. Correlation analysis showed that SFCT positively correlated with N1 and P1 amplitudes (r=0.270, 0.246; P<0.05) and negatively correlated with their latency periods (r=-0.219, -0.248; P<0.05). The ROC curve results indicated the cutoff values for SFCT were 192.75µm between Grade 1 and 2, 162µm between Grade 2 and 3, and 130.75µm between Grade 3 and 4.

Conclusion: Assessment in fundus tessellation using MfERG and OCTA contributes to objective grading of fundus tessellation and further help to clinical prediction and treatment.

Translational relevance: Assessment in fundus tessellation morphologically and functionally using MfERG and OCTA contributes to classification and clinical prediction of fundus tessellation.

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