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Navid Amini, Nila Cirineo, Shane Knipping, Hamid Hosseini, JoAnn Giaconi, Simon Law, Thomas Chou, Luminita Vese, Joseph Caprioli, Kouros Nouri-Mahdavi; Evaluation of Inner to Outer Retina Area Ratio for Detection of Glaucoma with Macular OCT Imaging. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4840.
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© ARVO (1962-2015); The Authors (2016-present)
To determine whether the inner to outer retina (OR) area ratio can improve detection of glaucoma with macular SD-OCT imaging as compared to ganglion cell/inner plexiform layer (GC/IPL) thickness measurements.
Forty-one normal subjects and 27 glaucoma patients from the UCLA OCT Imaging Study were included. Macular images were obtained (posterior pole algorithm, Spectralis SD-OCT) and the raw data files were exported for automatic segmentation of retinal layers using 3-D contextual information (Iowa OCT Explorer). Properties of the derivative of surface and thickness functions were exploited to locate the foveal center in MATLAB. The B-scan passing through the foveal center was used for computing the total area of inner and outer retina layers in the central 4.8mm of the scan. Average ganglion cell/inner plexiform layer (GC/IPL) measurements were also obtained (Macular Cube 200x200, Cirrus HD-OCT). Logistic regression and area under the ROC curves (AUCs) were used to compare models. Performance of ganglion cell complex and GC/IPL to OR (GCC/OR vs. GC/OR) area ratios were also compared.
The median (IQR) MD was −3.9 (−6.3 to −2.5) dB and 0 (−0.8 to 0.4) dB in glaucoma and normal subjects, respectively. The corresponding mean GC/OR area ratios were 0.27 (±0.05) and 0.33 (±0.03). GC/OR area ratio was not related to age or axial length in normal subjects (p>0.05). GC/IPL thickness and GC/OR ratio were highly correlated (p<0.001) in normal (R2=0.39) and glaucoma subjects (R2=0.74). AUCs for detection of glaucoma were similar for GC/IPL (0.90) or GC/OR area ratio (0.88) when adjusted for age and axial length. GC/OR area ratio and its interaction with average GC/IPL were found to be significantly predictive of glaucoma (p=0.005 and 0.009, respectively) when added to GC/IPL. This improved the predictive performance of the logistic regression compared to GC/IPL alone (AUC for the combined model=0.93; p=0.09 for comparison to GC/IPL model). The results were similar when GCC/OR area ratio was used.
GC/OR area ratio does not vary as a function of age or axial length in normal subjects. Adding GC/OR area ratio to GC/IPL thickness in multivariate predictive models can potentially improve detection of glaucoma.
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