title: Quantifying discordance between structure and function measurements in the clinical assessment of glaucoma.
abstract: OBJECTIVE
  To evaluate a new method of quantifying and visualizing discordance between structural and functional measurements in glaucomatous eyes by predicting the visual field (VF) from retinal nerve fiber layer thickness (RNFLT) using a bayesian radial basis function.
  
  
  METHODS
  Five GDx VCC RNFLT scans and 5 Humphrey 24-2 Swedish Interactive Thresholding Algorithm VF tests were performed for 50 glaucomatous eyes from 50 patients. A best-available estimate (BAE) of the true VF was calculated as the pointwise median of these 5 replications. This BAE VF was compared with every RNFLT-predicted VF from the bayesian radial basis function and every measured VF. Predictability of VFs from RNFLT was established from previous data. A structure-function pattern discordance map and a structure-function discordance index (scores of 0-1) were established from the predictability limits for each structure-function measurement pair to quantify and visualize the discordance between the structure-predicted and measured VFs.
  
  
  RESULTS
  The mean absolute difference between the structure-predicted and BAE VFs was 3.9 dB. The mean absolute difference between measured and BAE VFs was 2.6 dB. The mean (SD) structure-function discordance index score was 0.34 (0.11). Ninety-seven (39%) of the structure-predicted VFs showed significant discordance (structure-function discordance index score >0.3) from measured VFs.
  
  
  CONCLUSIONS
  On average, the bayesian radial basis function predicts the BAE VF from RNFLT slightly less well than a measured VF from the 5 VFs composing the BAE VF. The pattern discordance map highlights locations with structure-function discordance, with the structure-function discordance index providing a summary index. These tools may help clinicians trust the mutually confirmatory structure-function measurements with good concordance or identify unreliable ones with poor concordance.
authors.affiliation: Department of Optometry and Visual Science, City University London, London, England.
authors.forename: Haogang
authors.initials: H
authors.lastname: Zhu
authors.forename: David P
authors.initials: DP
authors.lastname: Crabb
authors.forename: Marie-Josée
authors.initials: MJ
authors.lastname: Fredette
authors.forename: Douglas R
authors.initials: DR
authors.lastname: Anderson
authors.forename: David F
authors.initials: DF
authors.lastname: Garway-Heath
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003941:Diagnostic Techniques, Ophthalmological; D005901:Glaucoma / Q000175:diagnosis*; D006801:Humans; D007429:Intraocular Pressure; D009412:Nerve Fibers / Q000473:pathology*; D009901:Optic Nerve Diseases / Q000175:diagnosis*; D012165:Retinal Ganglion Cells / Q000473:pathology*; D041623:Tomography, Optical Coherence; D014065:Tonometry, Ocular; D014786:Vision Disorders / Q000175:diagnosis*; D058609:Visual Field Tests; D014794:Visual Fields