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SYMPOSIUM - TRIP
Year : 2014  |  Volume : 62  |  Issue : 1  |  Page : 82-87

Scanning the macula for detecting glaucoma


1 VST Glaucoma Center, L V Prasad Eye Institute, Banjara Hills, Hyderabad, Andhra Pradesh, India
2 VST Glaucoma Center; Center for Clinical Epidemiology and Biostatistics, L V Prasad Eye Institute, Banjara Hills, Hyderabad, Andhra Pradesh, India

Correspondence Address:
Harsha L Rao
Kallam Anji Reddy campus, L V Prasad Eye Institute, Banjara Hills, Hyderabad - 500 034, Andhra Pradesh
India
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Source of Support: Begum VU: none; Jonnadula GB: none; Yadav RK: none; Addepalli UK: none; Senthil S: none; Choudhari NS: none; Garudadri CS: Allergan (C), Merck (C), Alcon (C), Optovue (F); Rao HL: Allergan (C)., Conflict of Interest: None


DOI: 10.4103/0301-4738.126188

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Background: With the advent of spectral domain optical coherence tomography (SDOCT), there has been a renewed interest in macular region for detection of glaucoma. However, most macular SDOCT parameters currently are thickness parameters which evaluate thinning of the macular layers but do not quantify the extent of area over which the thinning has occurred. We therefore calculated a new macular parameter, "ganglion cell complex surface abnormality ratio (GCC SAR)" that represented the surface area over which the macular thickness was decreased. Purpose: To evaluate the ability of SAR in detecting perimetric and preperimetric glaucoma. Design: Retrospective image analysis. Materials and Methods: 68 eyes with perimetric glaucoma, 62 eyes with preperimetric glaucoma and 165 control eyes underwent GCC imaging with SDOCT. SAR was calculated as the ratio of the abnormal to total area on the GCC significance map. Statistical Analysis: Diagnostic ability of SAR in glaucoma was compared against that of the standard parameters generated by the SDOCT software using area under receiver operating characteristic curves (AUC) and sensitivities at fixed specificities. Results: AUC of SAR (0.91) was statistically significantly better than that of GCC average thickness (0.86, P = 0.001) and GCC global loss volume (GLV; 0.88, P = 0.01) in differentiating perimetric glaucoma from control eyes. In differentiating preperimetric glaucoma from control eyes, AUC of SAR (0.72) was comparable to that of GCC average thickness (0.70, P > 0.05) and GLV (0.72, P > 0.05). Sensitivities at specificities of 80% and 95% of SAR were comparable (P > 0.05 for all comparisons) to that of GCC average thickness and GLV in diagnosing perimetric and preperimetric glaucoma. Conclusion: GCC SAR had a better ability to diagnose perimetric glaucoma compared to the SDOCT software provided global GCC parameters. However, in diagnosing preperimetric glaucoma, the ability of SAR was similar to that of software provided global GCC parameters.


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