June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Peripapillary Retinal Vessel Density as an Ocular Biomarker for Schizophrenia
Author Affiliations & Notes
  • Caroline Simon
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Kevin Zhang
    Creighton University School of Medicine, Omaha, Nebraska, United States
  • Victoria Chen
    Ophthalmology and Visual Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Erik Gunnarsson
    University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Hugh O'Neill
    Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Elliot Hong
    Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Osamah Saeedi
    Ophthalmology and Visual Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Caroline Simon None; Kevin Zhang None; Victoria Chen None; Erik Gunnarsson None; Hugh O'Neill None; Elliot Hong None; Osamah Saeedi Aerie Pharmaceuticals, Code F (Financial Support), Heidelberg Engineering, Code F (Financial Support), Vasoptic Medical, Code F (Financial Support)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2934 – F0087. doi:
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      Caroline Simon, Kevin Zhang, Victoria Chen, Erik Gunnarsson, Hugh O'Neill, Elliot Hong, Osamah Saeedi; Peripapillary Retinal Vessel Density as an Ocular Biomarker for Schizophrenia. Invest. Ophthalmol. Vis. Sci. 2022;63(7):2934 – F0087.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Retinal pathology has been linked to neurodegenerative diseases. Schizophrenia is a neurodegenerative disease with major research gaps and significant burden to society. Discovery of ocular biomarkers could lead to earlier diagnosis and improved outcomes for patients with schizophrenia. Additionally, identifying ocular manifestations of schizophrenia can lead to an improved understanding of the disease pathophysiology. In this study, we sought to examine the link between schizophrenia spectrum disorders (SSD) and vessel density in participant’s optic nerve head (ONH) regions of the retina using Optical Coherence Tomography Angiography (OCTA).

Methods : The study included 73 SSD patients and 57 age-matched healthy controls. Schizophrenia diagnosis was confirmed through structured diagnostic interviews. OCTA was used to noninvasively image retinal vessels in the whole retinal thickness (WR) and superficial capillary plexus (SCP) of the ONH region. OCTA images were binarized using the Phansalkar threshold method and subsequently skeletonized in ImageJ (image 1).

Results : The mean binarized vessel densities for the controls and SSD in the WR were 64.1±4.0 and 65.1±3.0, respectively (p=0.12). Skeletonized vessel densities in the WR were 15.5±0.8 in the controls and 15.7±0.6 in SSD (p=0.30). In the SCP, the binarized vessel densities were 61.5±2.8 in the controls and 62.0±3.3 in SSD (p=0.39). The mean skeletonized densities in the SCP were 15.0±0.6 in the controls and 15.0±0.7 in SSD (p=0.74).

Conclusions : Phansalkar binarization and skeletonization of retinal OCTA images did not find significant differences in vessel density in the ONH regions between schizophrenia patients and healthy controls. Vessel density in the ONH region of the retina of patients with schizophrenia may provide an important tool in the diagnosis and further understanding of the disease.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

Image 1. OCTA image of the ONH region of a participant's retina (left). Same OCTA image with Phansalkar binarization applied (middle) and with Phansalkar binarization + skeletonization applied (right).

Image 1. OCTA image of the ONH region of a participant's retina (left). Same OCTA image with Phansalkar binarization applied (middle) and with Phansalkar binarization + skeletonization applied (right).

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