Association of retinal microvascular abnormalities and neuromyelitis optica spectrum disorders with optical coherence tomography angiography

Jiaqi Guo; Dan Zhang; Yan Gong; Jiang Liu; Jiong Zhang; Yitian Zhao

doi:10.3389/fnins.2023.1194661

Association of retinal microvascular abnormalities and neuromyelitis optica spectrum disorders with optical coherence tomography angiography

Front Neurosci. 2023 Jun 9:17:1194661. doi: 10.3389/fnins.2023.1194661. eCollection 2023.

Authors

Jiaqi Guo^#^{1

2}, Dan Zhang^#³, Yan Gong⁴, Jiang Liu⁵, Jiong Zhang^{1

4}, Yitian Zhao^{1

4}

Affiliations

¹ Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
² University of Chinese Academy of Sciences, Beijing, China.
³ School of Cyber Science and Engineering, Ningbo University of Technology, Ningbo, China.
⁴ The Affiliated Ningbo Eye Hospital of Wenzhou Medical University, Ningbo, China.
⁵ Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China.

^# Contributed equally.

Abstract

Introduction: Neuromyelitis optica spectrum disorders (NMOSD) are autoimmune central nervous system diseases characterized by the immune system's abnormal attack on glial cells and neurons. Optic neuritis (ON) is one of the indicators of NMOSD, often starting unilaterally and potentially affecting both eyes later in the disease progression, leading to visual impairment. Optical coherence tomography angiography (OCTA) has the potential to aid in the early diagnosis of NMOSD by examining ophthalmic imaging and may offer a window for disease prevention.

Methods: In this study, we collected OCTA images from 22 NMOSD patients (44 images) and 25 healthy individuals (50 images) to investigate retinal microvascular changes in NMOSD. We employed effective retinal microvascular segmentation and foveal avascular zone (FAZ) segmentation techniques to extract key OCTA structures for biomarker analysis. A total of 12 microvascular features were extracted using specifically designed methods based on the segmentation results. The OCTA images of NMOSD patients were classified into two groups: optic neuritis (ON) and non-optic neuritis (non-ON). Each group was compared separately with a healthy control (HC) group.

Results: Statistical analysis revealed that the non-ON group displayed shape changes in the deep layer of the retina, specifically in the FAZ. However, there were no significant microvascular differences between the non-ON group and the HC group. In contrast, the ON group exhibited microvascular degeneration in both superficial and deep retinal layers. Sub-regional analysis revealed that pathological variations predominantly occurred on the side affected by ON, particularly within the internal ring near the FAZ.

Discussion: The findings of this study highlight the potential of OCTA in evaluating retinal microvascular changes associated with NMOSD. The shape alterations observed in the FAZ of the non-ON group suggest localized vascular abnormalities. In the ON group, microvascular degeneration in both superficial and deep retinal layers indicates more extensive vascular damage. Sub-regional analysis further emphasizes the impact of optic neuritis on pathological variations, particularly near the FAZ's internal ring.

Conclusion: This study provides insights into the retinal microvascular changes associated with NMOSD using OCTA imaging. The identified biomarkers and observed alterations may contribute to the early diagnosis and monitoring of NMOSD, potentially offering a time window for intervention and prevention of disease progression.

Keywords: OCTA; deep learning; neuromyelitis optica spectrum disorders; retinal microvascular; segmentation.

Grants and funding

This work was supported in part by the Zhejiang Provincial Natural Science Foundation (LQ23F010002, LR22F020008, and LZ19F010001), in part by the Ningbo Natural Science Foundation (2022J143 and 20221JCGY010608) and the Scientific Research Program of Zhejiang Provincial Department of Education (Y202250360), in part by the Youth Innovation Promotion Association CAS (2021298), the Research Startup Fund of Ningbo University of Technology (2022KQ29), and in part by 2025 S&T Megaprojects (2019B10033, 2019B10061, and 2021Z054).