Accuracy of scanning laser polarimetry in the diagnosis of glaucoma

Arch Ophthalmol. 1999 Oct;117(10):1298-304. doi: 10.1001/archopht.117.10.1298.


Objective: To determine the diagnostic accuracy of scanning laser polarimetry.

Subjects and methods: A total of 95 healthy subjects and 102 patients with glaucoma met all inclusion criteria. Data collected on each participant included an automated visual field examination, stereoview optic nerve head photographs, intraocular pressure measurement, and a screening and full scanning laser polarimetry study. Each participant was classified as "normal," "glaucoma," or "uncertain" by each of 3 ophthalmologists based on all available clinical information, with the exception of the scanning laser polarimetry results. Before data analysis, 4 diagnostic algorithms for the full-test mode and 2 for the screening mode were chosen to be evaluated for their sensitivity and specificity in detecting glaucoma.

Results: Of the 4 algorithms tested for the full-test mode, "the number" (abnormal test score, >35) had sensitivities of 57%, 71%, and 81% for early, moderate, and severe glaucoma, respectively. Specificity was 89%. For the screening test, sensitivities were much lower, particularly for those with severe glaucoma damage.

Conclusions and clinical relevance: Scanning laser polarimetry can help to differentiate subjects with normal findings from patients with glaucomatous damage. Even the best algorithm tested, however, failed to detect a substantial number of subjects with severe damage. Further study is needed before scanning laser polarimetry can be recommended as a screening method for glaucoma.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms
  • Diagnostic Techniques, Ophthalmological*
  • Female
  • Glaucoma / diagnosis*
  • Humans
  • Intraocular Pressure
  • Lasers*
  • Male
  • Nerve Fibers / pathology*
  • Optic Nerve / pathology*
  • ROC Curve
  • Reproducibility of Results
  • Retina / pathology*
  • Sensitivity and Specificity
  • Visual Fields