Compensation of retinal nerve fibre layer thickness as assessed using optical coherence tomography based on anatomical confounders

Br J Ophthalmol. 2020 Feb;104(2):282-290. doi: 10.1136/bjophthalmol-2019-314086. Epub 2019 May 22.

Abstract

Background/aims: To compensate the retinal nerve fibre layer (RNFL) thickness assessed by spectral-domain optical coherence tomography (SD-OCT) for anatomical confounders.

Methods: The Singapore Epidemiology of Eye Diseases is a population-based study, where 2698 eyes (1076 Chinese, 704 Malays and 918 Indians) with high-quality SD-OCT images from individuals without eye diseases were identified. Optic disc and macular cube scans were registered to determine the distance between fovea and optic disc centres (fovea distance) and their respective angle (fovea angle). Retinal vessels were segmented in the projection images and used to calculate the circumpapillary retinal vessel density profile. Compensated RNFL thickness was generated based on optic disc (ratio, orientation and area), fovea (distance and angle), retinal vessel density, refractive error and age. Linear regression models were used to investigate the effects of clinical factors on RNFL thickness.

Results: Retinal vessel density reduced significantly with increasing age (1487±214 µm in 40-49, 1458±208 µm in 50-59, 1429±223 µm in 60-69 and 1415±233 µm in ≥70). Compensation reduced the variability of RNFL thickness, where the effect was greatest for Chinese (10.9%; p<0.001), followed by Malays (6.6%; p=0.075) and then Indians (4.3%; p=0.192). Compensation reduced the age-related RNFL decline by 55% in all participants (β=-3.32 µm vs β=-1.50 µm/10 years; p<0.001). Nearly 62% of the individuals who were initially classified as having abnormally thin RNFL (outside the 99% normal limits) were later reclassified as having normal RNFL.

Conclusions: RNFL thickness compensated for anatomical parameters reduced the variability of measurements and may improve glaucoma detection, which needs to be confirmed in future studies.

Keywords: imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Aging / pathology
  • Ethnicity
  • Female
  • Humans
  • Male
  • Middle Aged
  • Nerve Fibers / pathology*
  • Regression Analysis
  • Retinal Ganglion Cells / cytology*
  • Retinal Vessels / cytology*
  • Tomography, Optical Coherence / methods