Variance in the macular sublayers' volume as a diagnostic tool for primary open-angle glaucoma
- PMID: 35869403
- DOI: 10.1007/s10792-022-02425-z
Variance in the macular sublayers' volume as a diagnostic tool for primary open-angle glaucoma
Abstract
Purpose: To assess the variance of macular sublayers' volume in glaucoma patients compared with normal individuals.
Methods: This case-control observational study included 63 cases of primary open-angle glaucoma and 57 healthy controls. Macular volumetric scans were captured at the 6 mm ETDRS circle for each retinal sublayer using Spectralis OCT2. The studied macular sublayers included the retinal nerve fiber layer, ganglion cell layer, inner plexiform layer, inner nuclear layer, outer plexiform layer, outer nuclear layer, and outer retinal layers (external limiting membrane to the retinal pigment epithelium). Standard deviation (SD) and coefficient of variation (CoV) of macular sublayers' volume were calculated. An unpaired Student t test (or its nonparametric equivalent) was used to compare each variable between groups. The receiver operating characteristic curve (ROC) was used to investigate the discriminative ability of each parameter.
Results: There was no significant difference for age or sex between the groups. The SD (of all sublayers' volume) was greater in the glaucomatous eyes compared with controls (0.620 ± 0.073vs.0.524 ± 0.056 mm3, respectively; P < 0.001). The same pattern was observed for CoV (7.890 ± 0.979vs.6.128 ± 0.583; P < 0.001). The area under curves (AUCs) for SD and CoV were 0.855and0.930, respectively (P = 0.05). The best cutoff value for the CoV was 6.712. The CoV and ganglion cell layer (GCL) volume revealed similar sensitivity (80.75) at 95% specificity for diagnosing glaucoma. The CoV detected 5 patients with glaucoma who had normal GCC volume.
Conclusion: This study showed that the macular sublayers' volume variance parameters could be viable OCT biomarkers for detecting glaucomatous changes.
Keywords: Coefficient of variation; Glaucoma; Optical coherence tomography; Segmentation; Standard deviation.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.
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