Retinal nerve fiber layer reflectance for early glaucoma diagnosis.

Published

Journal Article

PURPOSE: Compare performance of normalized reflectance index (NRI) and retinal nerve fiber layer thickness (RNFLT) parameters determined from optical coherence tomography (OCT) images for glaucoma and glaucoma suspect diagnosis. METHODS: Seventy-five eyes from 71 human subjects were studied: 33 controls, 24 glaucomatous, and 18 glaucoma-suspects. RNFLT and NRI maps were measured using 2 custom-built OCT systems and the commercial instrument RTVue. Using area under the receiver operating characteristic curve, RNFLT and NRI measured in 7 RNFL locations were analyzed to distinguish between control, glaucomatous, and glaucoma-suspect eyes. RESULTS: The mean NRI of the control group was significantly larger than the means of glaucomatous and glaucoma-suspect groups in most RNFL locations for all 3 OCT systems (P<0.05 for all comparisons). NRI performs significantly better than RNFLT at distinguishing between glaucoma-suspect and control eyes using RTVue OCT (P=0.008). The performances of NRI and RNFLT for classifying glaucoma-suspect versus control eyes were statistically indistinguishable for PS-OCT-EIA (P=0.101) and PS-OCT-DEC (P=0.227). The performances of NRI and RNFLT for classifying glaucomatous versus control eyes were statistically indistinguishable (PS-OCT-EIA: P=0.379; PS-OCT-DEC: P=0.338; RTVue OCT: P=0.877). CONCLUSIONS: NRI is a promising measure for distinguishing between glaucoma-suspect and control eyes and may indicate disease in the preperimetric stage. Results of this pilot clinical study warrant a larger study to confirm the diagnostic power of NRI for diagnosing preperimetric glaucoma.

Full Text

Duke Authors

Cited Authors

  • Liu, S; Wang, B; Yin, B; Milner, TE; Markey, MK; McKinnon, SJ; Rylander, HG

Published Date

  • January 2014

Published In

Volume / Issue

  • 23 / 1

Start / End Page

  • e45 - e52

PubMed ID

  • 23835671

Pubmed Central ID

  • 23835671

Electronic International Standard Serial Number (EISSN)

  • 1536-481X

Digital Object Identifier (DOI)

  • 10.1097/IJG.0b013e31829ea2a7

Language

  • eng

Conference Location

  • United States