title: Impact of segmentation errors and retinal blood vessels on retinal nerve fibre layer measurements using spectral-domain optical coherence tomography.
abstract: OBJECTIVE
  To investigate the impact of retinal blood vessels and retinal nerve fibre layer (RNFL) segmentation errors on RNFL measurement.
  
  
  METHODS
  One eye of 180 subjects (60 normal, 66 mild-to-moderate and 54 advanced glaucoma subjects) was randomly selected for RNFL imaging with a spectral-domain OCT. The boundaries of the RNFL detected by the instrument software were checked, and the segmentation errors were corrected by a customized computer program. The differences in average and regional RNFL thicknesses (RNFLT) before and after the correction were analysed to determine the frequency of segmentation error (defined as an absolute difference in average RNFLT >5.0 μm). The ratio of retinal blood vessel cross-sectional area to RNFL cross-sectional area was calculated.
  
  
  RESULTS
  The difference in average RNFLT (postsegmentation minus presegmentation refinement) ranged from -3.0 to 2.5 μm (mean ± standard deviation: 0.83 ± 0.86 μm) in the normal, -2.5 to 5.0 μm (0.56 ± 1.08 μm) in the mild-to-moderate glaucoma and -11.0 to 9.5 μm (0.05 ± 3.49 μm) in the advanced glaucoma groups (p = 0.003). A total of 15% of eyes had average RNFLT measurement error >5.0 μm in the advanced glaucoma group. The proportion of retinal blood vessels in the RNFL also increased with the severity of glaucoma (p < 0.001) with 4.2 ± 1.0% in the normal group, 4.9 ± 1.5% in the mild-to-moderate and 8.5 ± 3.5% in the advanced glaucoma groups.
  
  
  CONCLUSIONS
  Inclusion of retinal blood vessels and RNFL segmentation error could adversely affect RNFL measurement, particularly in advanced glaucoma when the RNFL was thin.
authors.affiliation: Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China.
authors.forename: Cong
authors.initials: C
authors.lastname: Ye
authors.affiliation: Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China.|Department of Mathematics and Statistics, Hang Seng Management College, Hong Kong, China.
authors.forename: Marco
authors.initials: M
authors.lastname: Yu
authors.affiliation: Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong, China.
authors.forename: Christopher Kai-Shun
authors.initials: CK
authors.lastname: Leung
mesh_terms: D000328:Adult; D003430:Cross-Sectional Studies; D003951:Diagnostic Errors; D018450:Disease Progression; D005260:Female; D005901:Glaucoma / Q000175:diagnosis*; D006068:Gonioscopy; D006801:Humans; D007429:Intraocular Pressure / Q000502:physiology; D008297:Male; D008875:Middle Aged; D009412:Nerve Fibers / Q000473:pathology*; D009901:Optic Nerve Diseases / Q000175:diagnosis*; D012165:Retinal Ganglion Cells / Q000473:pathology*; D012171:Retinal Vessels / Q000473:pathology*; D041623:Tomography, Optical Coherence; D014792:Visual Acuity / Q000502:physiology; D014794:Visual Fields / Q000502:physiology
keywords: glaucoma; image analysis; optical coherence tomography; retinal blood vessels; retinal nerve fibre layer; segmentation