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Detection of glaucoma progression by population and individual derived variability criteria
  1. Lindsey S Folio1,2,
  2. Gadi Wollstein1,
  3. Jacek Kotowski1,
  4. Richard A Bilonick1,3,
  5. Yun Ling1,3,
  6. Hiroshi Ishikawa1,2,
  7. Larry Kagemann1,2,
  8. Joel S Schuman1,2
  1. 1UPMC Eye Center, Eye & Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
  2. 2Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  3. 3Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  1. Correspondence to Dr Gadi Wollstein, UPMC Eye Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, 203 Lothrop Street, Eye and Ear Institute, Suite 834, Pittsburgh, PA 15213, USA;wollsteing{at}upmc.edu.

Abstract

Purpose Ocular imaging devices provide quantitative structural information that might improve glaucoma progression detection. This study examined scanning laser polarimetry (SLP) population-derived versus individual-derived cut-off criteria for detecting progression.

Methods Forty-eight healthy, glaucoma suspect and glaucoma subjects, providing 76 eyes were used. All subjects had reliable visual field (VF) and SLP scans acquired at the same visits from ≥4 visits. VF progression was defined by guided progression analysis (GPA) and by the VF index. SLP measurements were analysed by fast mode (FM) GPA, compared with the population rate of progression, and extended mode (EM) GPA, compared with the individual variability. The agreement between progression detection methods was measured.

Results Poor agreement was observed between progression defined by VF and FM and EM. The difference in temporal-superior-nasal-inferior-temporal (TSNIT) average rate of change between VF defined progressors and non-progressors for both FM (p=0.010) and EM (p=0.015) was statistically significant.

Conclusions There is poor agreement between VF and SLP progression regardless of the use of population derived or individual variability criteria. The best SLP progression detection method could not be ascertained, therefore, acquiring three SLP scans per visit is recommended.

  • Glaucoma
  • Imaging

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