Significant structure-function associations were found between GCIPL thickness measurements at the macula and the functional loss measured on 10-2 SAP in glaucoma. Best fit was found for the inferior and average GCIPL sector thickness. The linear model was useful to study the structure-function relationship.
PurposeTo compare the diagnostic abilities of structural (ganglion cell-inner plexiform layer (GCIPL) thickness measured using spectral domain optical coherence tomography (SDOCT)) and functional (visual sensitivities measured using standard automated perimetry (SAP) and microperimetry (MP)) assessments of macula in glaucoma.MethodsIn a prospective study, 46 control eyes (28 subjects) and 61 glaucoma eyes (46 patients) underwent visual sensitivity estimation at macula (central 10°) by SAP and MP, and GCIPL thickness measurement at macula by SDOCT. Glaucoma was diagnosed by experts based on the optic disc and retinal nerve fiber layer changes. Area under the receiver-operating characteristic (AUC) curves and sensitivities at 95% specificity were used to assess the diagnostic ability of visual sensitivity and GCIPL measurements at various macular sectors.ResultsAUCs of GCIPL parameters ranged between 0.58 and 0.79. AUCs of SAP and MP sensitivities ranged between 0.59 and 0.71, and 0.59 and 0.72, respectively. There were no statistically significant differences between the AUCs of corresponding sector measurements (P>0.10 for all comparisons). Sensitivities at 95% specificities ranged from 31-59% for GCIPL parameters, 16-34% for SAP, and 8-38% for MP parameters. Sensitivities were significantly better with GCIPL compared with SAP and MP parameters in diagnosing glaucoma. Inferotemporal, inferior, and superotemporal sector measurements of GCIPL and visual sensitivity showed the best abilities to diagnose glaucoma.ConclusionsComparing the diagnostic abilities of structural and functional tests at macula in glaucoma, GCIPL thickness measurements with SDOCT performed better than the visual sensitivity measurements by SAP and MP.
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