Clinical Utility of Bruch Membrane Opening-Minimum Rim Width for Detecting Early Glaucoma in Myopic Eyes

Evaluating glaucoma in myopic eyes: Challenges and opportunities

The increasing global prevalence of myopia presents a significant public health concern, and growing evidence has demonstrated that myopia is a major risk factor for the development of open-angle glaucoma. Therefore, timely detection and management of glaucoma in myopic patients are crucial; however, identifying the structural alterations of glaucoma in the optic nerve head (ONH) and retinal tissues of myopic eyes using standard diagnostic tools such as fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA) presents challenges. Additionally, myopia-related perimetric defects can be confounded with glaucoma-related defects. We comprehensively examine the challenges encountered in evaluating glaucoma in myopic eyes through various diagnostic tools, including fundus photography, OCT of the ONH, retinal nerve fiber layer, and macular ganglion cell layer, OCTA, and perimetry. We also explore potential opportunities to address these challenges, providing insights for clinicians to effectively manage myopic glaucoma patients in clinical practice.

Evaluation of the Inner Macula Layers, Circumpapillary Retinal Nerve Fiber Layer, and Minimum Rim Width Thickness in Patients With Pseudoexfoliation Syndrome Without Glaucoma Compared With Controls

PRCIS

Minimum rim width (MRW) is thinner in patients with non-glaucomatous pseudoexfoliation syndrome (XFS) and may be the first parameter affected in these patients due to the vascular nature of this disease.

OBJECTIVE

To evaluate the macular inner layers, circumpapillary retinal nerve fiber layer (cp-RNFL), and MRW in non-glaucomatous XFS compared with healthy patients.

PATIENTS AND METHODS

In this prospective study, using Heidelberg Spectralis optical coherence tomography with Glaucoma Module Premium Edition, 8×8 grids of macular inner layers were exported, and the global, superior, and inferior thicknesses were used. Also, on the deviation map, the elliptical annulus around the fovea, which was 4.8×4 mm in size, was analyzed. Moreover, both groups calculated cp-RNFL and MRW values in 3 superior and 3 inferior sectors.

RESULTS

Thirty-two eyes of 32 patients with clinically detected non-glaucomatous XFS and 30 right eyes of age-sex-matched healthy controls were included. No significant difference was found between the case and control groups concerning the intraocular pressure (14.94 ± 2.09 vs 15.27 ± 2.27 mm Hg, respectively, P = 0.556). The MRW of the superotemporal segment (MRW-temporal superior) was significantly thinner in the XFS group compared with the control ones (303.69 ± 60.49 vs 341.43 ± 56.19 µm, P = 0.014). No significant differences were found in the other sectors of MRW, macular inner layers, and cp-RNFL thickness between the groups.

CONCLUSION

These findings indicate that the MRW, especially in the superotemporal sector, may show early eye damage in patients with non-glaucomatous XFS, and it may be used to detect the early stage of glaucoma in XFS.

Deep learning classification of early normal-tension glaucoma and glaucoma suspect eyes using Bruch's membrane opening-based disc photography

Purpose

We aimed to investigate the performance of a deep learning model to discriminate early normal-tension glaucoma (NTG) from glaucoma suspect (GS) eyes using Bruch's membrane opening (BMO)-based optic disc photography.

Methods

501 subjects in total were included in this cross-sectional study, including 255 GS eyes and 246 eyes of early NTG patients. BMO-based optic disc photography (BMO overview) was obtained from spectral-domain optical coherence tomography (OCT). The convolutional neural networks (CNN) model built from scratch was used to classify between early NTG and GS. For diagnostic performances of the model, the accuracy and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) were evaluated in the test set.

Results

The baseline demographics were age, 48.01 ± 13.03 years in GS, 54.48 ± 11.28 years in NTG (p = 0.000); mean deviation, -0.73 ± 2.10 dB in GS, -2.80 ± 2.40 dB in NTG (p = 0.000); and intraocular pressure, 14.92 ± 2.62 mmHg in GS, 14.79 ± 2.61 mmHg in NTG (p = 0.624). Our CNN model showed the mean AUC of 0.94 (0.83-1.00) and the mean accuracy of 0.91 (0.82-0.98) with 10-fold cross validation for discriminating between early NTG and GS.

Conclusion

The performance of the CNN model using BMO-based optic disc photography was considerably good in classifying early NTG from GS. This new disc photography of BMO overview can aid in the diagnosis of early glaucoma.