Annals of Clinical and Translational Neurology (Sep 2024)

Retinal optical coherence tomography measures in multiple sclerosis: a systematic review and meta‐analysis

  • Nabil K. El Ayoubi,
  • Ali Ismail,
  • Fares Fahd,
  • Lama Younes,
  • Nour A. Chakra,
  • Samia J. Khoury

DOI
https://doi.org/10.1002/acn3.52165
Journal volume & issue
Vol. 11, no. 9
pp. 2236 – 2253

Abstract

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Abstract Spectral domain‐optical coherence tomography plays a crucial role in the early detection and monitoring of multiple sclerosis (MS) pathophysiology. We aimed to quantify differences in retinal layer measures among different groups of MS and explored different variables that correlate with retinal measures. This study was reported according PRISMA guidelines. A comprehensive search was done across PubMed, Embase, and Google Scholar. The mean difference in thickness of retinal layers and macular volume was assessed. Meta‐regression was done to assess the sources of heterogeneity. A total of 100 articles were included in the meta‐analyses. The peripapillary retinal nerve fiber layer (pRNFL) thickness significantly decreased in the MSON (MD: −16.44, P < 0.001), MSNON (MD: −6.97, P < 0.001), and PMS (MD: −11.35, P < 0.001) versus HC. The macular RNFL was lower among the MSON (MD: −6.24, P = 0.013) and MSNON (MD: −3.84, P <0.001) versus HC. Macular ganglion cell layer and inner plexiform layer (GCIPL) was thinner among MSON (MD: −14.83, P <0.001), MSNON (MD: −6.38, P < 0.001), and PMS (MD: −11.52, P < 0.001) compared with control eyes. Inner nuclear layer (INL) was higher in the MSON (MD: 0.49, P < 0.001) versus HC. Outer nuclear layer (ONL) thickness significantly lower in the MSNON (MD: −1.15, P = 0.019) versus HC. Meta‐regression showed that disease duration, age, EDSS score, and percentage of patients taking DMT are all negatively correlated with pRNFL and GCIPL thickness; however, female gender was correlated with less atrophy. As conclusion, the study highlights substantial thinning in the pRNFL and macular GCIPL between MS versus controls. INL as valuable parameter for capturing inflammatory disease activity.