June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Ability of spectral domain optical coherence tomography to diagnose preperimetric glaucoma
Author Affiliations & Notes
  • Chandrasekhar Garudadri
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Harsha Rao
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Uday Addepalli
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Shashi kant Chaudhary
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Tukaram Kumbar
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Sirisha Senthil
    Glaucoma, L V Prasad Eye Institute, Hyderabad, India
  • Footnotes
    Commercial Relationships Chandrasekhar Garudadri, Optovue (F); Harsha Rao, Allergan (C); Uday Addepalli, None; Shashi kant Chaudhary, None; Tukaram Kumbar, None; Sirisha Senthil, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 4828. doi:
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      Chandrasekhar Garudadri, Harsha Rao, Uday Addepalli, Shashi kant Chaudhary, Tukaram Kumbar, Sirisha Senthil; Ability of spectral domain optical coherence tomography to diagnose preperimetric glaucoma. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4828.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: To evaluate the ability of optic nerve head (ONH), retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) parameters of spectral domain optical coherence tomograph (SDOCT) in detecting preperimetric glaucoma.

Methods: We studied 261 eyes of 197 subjects referred to a tertiary eye care center by general ophthalmologists as glaucoma suspects based on optic disc appearance. All participants underwent comprehensive eye examination including visual fields, ONH, RNFL and GCC imaging with the commercially available SDOCT. The visual fields (VF) evaluated by standard automated perimetry were normal in all eyes. Two glaucoma experts masked to clinical, VF and imaging information independently classified the optic nerves into glaucoma and non-glaucoma groups based on digital optic disc photographs. Ability of SDOCT parameters to discriminate glaucoma (preperimetric) eyes from non-glaucoma (control) eyes was evaluated by areas under the receiver operating characteristic curves (AUC), sensitivities at fixed specificities of 80% and 95%, and likelihood ratios (LR).

Results: Experts classified 68 eyes of 60 patients as glaucomatous and 193 eyes of 137 subjects as controls. Age and VF characteristics were comparable between the groups. All SDOCT parameters were significantly different between the glaucomatous and control groups. ONH, RNFL and GCC parameters with best AUCs to differentiate preperimetric glaucoma from control eyes were inferior neuroretinal rim area (0.708), inferior quadrant RNFL thickness (0.713) and global loss volume (0.702) respectively. Sensitivities at 95% specificity for all these parameters were below 27%. LRs of outside normal limits category of the RNFL and GCC parameters were between 2.2 and 5.9, and within normal limits category were between 0.6 and 0.8. LRs of borderline category of SDOCT parameters were between 1 and 2.

Conclusions: Diagnostic abilities of ONH, RNFL and GCC parameters of SDOCT in preperimetric glaucoma were poor. This indicates a need for improvements in the current analysis algorithms of SDOCT for detection of preperimetric glaucoma.

Keywords: 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound)  
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