Peripapillary sclera exhibits a v-shaped configuration that is more pronounced in glaucoma eyes

Heterogenous thinning of peripapillary tissues occurs early during high myopia development in juvenile tree shrews

Myopia is an independent risk factor for glaucoma, but the link between both conditions remains unknown. Both conditions induce connective tissue remodeling at the optic nerve head (ONH), including the peripapillary tissues. The purpose of this study was to investigate the thickness changes of the peripapillary tissues during experimental high myopia development in juvenile tree shrews. Six juvenile tree shrews experienced binocular normal vision, while nine received monocular -10D lens treatment starting at 24 days of visual experience (DVE) to induce high myopia in one eye and the other eye served as control. Daily refractive and biometric measurements and weekly optical coherence tomography scans of the ONH were obtained for five weeks. Peripapillary sclera (Scl), choroid-retinal pigment epithelium complex (Ch-RPE), retinal nerve fiber layer (RNFL), and remaining retinal layers (RRL) were auto-segmented using a deep learning algorithm after nonlinear distortion correction. Peripapillary thickness values were quantified from 3D reconstructed segmentations. All lens-treated eyes developed high myopia (-9.8 ± 1.5 D), significantly different (P < 0.001) from normal (0.69 ± 0.45 D) and control eyes (0.76 ± 1.44 D). Myopic eyes showed significant thinning of all peripapillary tissues compared to both, normal and control eyes (P < 0.001). At the experimental end point, the relative thinning from baseline was heterogeneous across tissues and significantly more pronounced in the Scl (-8.95 ± 3.1%) and Ch-RPE (-16.8 ± 5.8%) when compared to the RNFL (-5.5 ± 1.6%) and RRL (-6.7 ± 1.8%). Furthermore, while axial length increased significantly throughout the five weeks of lens wear, significant peripapillary tissue thinning occurred only during the first week of the experiment (until a refraction of -2.5 ± 1.9 D was reached) and ceased thereafter. A sectorial analysis revealed no clear pattern. In conclusion, our data show that in juvenile tree shrews, experimental high myopia induces significant and heterogeneous thinning of the peripapillary tissues, where the retina seems to be protected from profound thickness changes as seen in Ch-RPE and Scl. Peripapillary tissue thinning occurs early during high myopia development despite continued progression of axial elongation. The observed heterogeneous thinning may contribute to the increased risk for pathological optic nerve head remodeling and glaucoma later in life.

Parapapillary gamma zone associated with increased peripapillary scleral bowing: the Beijing Eye Study 2011

AIMS

To investigate the association between the backward configuration of the peripapillary sclera (PPS), measured as PPS angle (PPSA), and presence and extent of parapapillary gamma zone.

METHODS

Out of the population-based Beijing Eye Study 2011, we randomly selected individuals free of optic nerve and retinal diseases. With Spectralis optical coherence tomography, we measured gamma zone (zone free of Bruch's membrane (BM)) and determined the PPSA, defined as the angle between the anterior scleral surface lines from both sides of the optic nerve head (ONH).

RESULTS

The study included 678 individuals with age of 59.5±7.6 years (range: 50-90) and axial length of 23.5±1.3 mm (20.9-29.2). Gamma zone was more prevalent in eyes with larger PPSA (p=0.006) after adjustment for axial length (p<0.001) and BM opening area (p<0.001). Gamma zone width was positively associated with PPSA, axial length and BM opening area (all p<0.001) in multivariable analysis. Circular gamma zone was accompanied with larger PPSA as compared with focal gamma zone (19.9°±7.2° vs 6.3°±5.3°, p<0.001). Focal temporal gamma and focal inferior gamma had similar mean PPSA (p=0.69). However, the horizontal PPSA was significantly larger than the vertical PPSA in inferior gamma (6.9°±6.3° vs 4.7°±6.6°; p=0.005), while they were comparable in temporal gamma (6.1°±5.8° vs 6.3°±6.4°; p=0.073).

CONCLUSIONS

A more backward bowing of the PPS was linearly and spatially associated with the presence, size and extent of gamma zone. It suggested that the BM and the sclera were closely related in participating the biomechanical behaviour of the ONH.

Three-Dimensional Structural Phenotype of the Optic Nerve Head as a Function of Glaucoma Severity

Importance

The 3-dimensional (3-D) structural phenotype of glaucoma as a function of severity was thoroughly described and analyzed, enhancing understanding of its intricate pathology beyond current clinical knowledge.

Objective

To describe the 3-D structural differences in both connective and neural tissues of the optic nerve head (ONH) between different glaucoma stages using traditional and artificial intelligence-driven approaches.

Design, Setting, and Participants

This cross-sectional, clinic-based study recruited 541 Chinese individuals receiving standard clinical care at Singapore National Eye Centre, Singapore, and 112 White participants of a prospective observational study at Vilnius University Hospital Santaros Klinikos, Vilnius, Lithuania. The study was conducted from May 2022 to January 2023. All participants had their ONH imaged using spectral-domain optical coherence tomography and had their visual field assessed by standard automated perimetry.

Main Outcomes and Measures

(1) Clinician-defined 3-D structural parameters of the ONH and (2) 3-D structural landmarks identified by geometric deep learning that differentiated ONHs among 4 groups: no glaucoma, mild glaucoma (mean deviation [MD], ≥-6.00 dB), moderate glaucoma (MD, -6.01 to -12.00 dB), and advanced glaucoma (MD, <-12.00 dB).

Results

Study participants included 213 individuals without glaucoma (mean age, 63.4 years; 95% CI, 62.5-64.3 years; 126 females [59.2%]; 213 Chinese [100%] and 0 White individuals), 204 with mild glaucoma (mean age, 66.9 years; 95% CI, 66.0-67.8 years; 91 females [44.6%]; 178 Chinese [87.3%] and 26 White [12.7%] individuals), 118 with moderate glaucoma (mean age, 68.1 years; 95% CI, 66.8-69.4 years; 49 females [41.5%]; 97 Chinese [82.2%] and 21 White [17.8%] individuals), and 118 with advanced glaucoma (mean age, 68.5 years; 95% CI, 67.1-69.9 years; 43 females [36.4%]; 53 Chinese [44.9%] and 65 White [55.1%] individuals). The majority of ONH structural differences occurred in the early glaucoma stage, followed by a plateau effect in the later stages. Using a deep neural network, 3-D ONH structural differences were found to be present in both neural and connective tissues. Specifically, a mean of 57.4% (95% CI, 54.9%-59.9%, for no to mild glaucoma), 38.7% (95% CI, 36.9%-40.5%, for mild to moderate glaucoma), and 53.1 (95% CI, 50.8%-55.4%, for moderate to advanced glaucoma) of ONH landmarks that showed major structural differences were located in neural tissues with the remaining located in connective tissues.

Conclusions and Relevance

This study uncovered complex 3-D structural differences of the ONH in both neural and connective tissues as a function of glaucoma severity. Future longitudinal studies should seek to establish a connection between specific 3-D ONH structural changes and fast visual field deterioration and aim to improve the early detection of patients with rapid visual field loss in routine clinical care.

OCT Optic Nerve Head Morphology in Myopia II: Peri-Neural Canal Scleral Bowing and Choroidal Thickness in High Myopia-An American Ophthalmological Society Thesis

PURPOSE

To use optical coherence tomography (OCT) to characterize optic nerve head (ONH) peri-neural canal (pNC) scleral bowing (pNC-SB) and pNC choroidal thickness (pNC-CT) in 69 highly myopic and 138 healthy, age-matched, control eyes.

DESIGN

Cross-sectional, case control study.

METHODS

Within ONH radial B-scans, Bruch membrane (BM), BM opening (BMO), anterior scleral canal opening (ASCO), and pNC scleral surface were segmented. BMO and ASCO planes and centroids were determined. pNC-SB was characterized within 30° foveal-BMO (FoBMO) sectors by 2 parameters: pNC-SB-scleral slope (pNC-SB-SS), measured within 3 pNC segments (0-300, 300-700, and 700-1000 μm from the ASCO centroid); and pNC-SB-ASCO depth relative to a pNC scleral reference plane (pNC-SB-ASCOD). pNC-CT was calculated as the minimum distance between the scleral surface and BM at 3 pNC locations (300, 700, and 1100 μm from the ASCO).

RESULTS

pNC-SB increased and pNC-CT decreased with axial length (P < .0133; P < .0001) and age (P < .0211; P < .0004) among all study eyes. pNC-SB was increased (P < .001) and pNC-CT was decreased (P < .0279) in the highly myopic compared to control eyes, and these differences were greatest in the inferior quadrant sectors (P < .0002). Sectoral pNC-SB was not related to sectoral pNC-CT in control eyes, but was inversely related to sectoral pNC-CT (P < .0001) in the highly myopic eyes.

CONCLUSIONS

Our data suggest that pNC-SB is increased and pNC-CT is decreased in highly myopic eyes and that these phenomena are greatest in the inferior sectors. They support the hypothesis that sectors of maximum pNC-SB may predict sectors of greatest susceptibility to aging and glaucoma in future longitudinal studies of highly myopic eyes. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Deep Optic Nerve Head Structures Associated With Increasing Axial Length in Healthy Myopic Eyes of Moderate Axial Length

PURPOSE

To elucidate which swept-source optical coherence tomography (OCT)-derived optic nerve head (ONH) parameters are associated with longer axial length (AXL) in healthy myopic eyes.

DESIGN

Prospective cross-sectional observational study.

METHODS

Two hundred eleven healthy eyes of 140 participants (96 emmetropic-mild myopic [AXL: 22.2-24.5 mm], 83 moderately myopic [24.5-26.0 mm], and 32 highly myopic [26.0-27.4 mm] eyes) were enrolled. Bruch membrane opening (BMO), anterior scleral canal opening (ASCO) area and ovality, minimum rim width, parameters defining misalignment between the BMO and ASCO planes, OCT-defined region of perineural canal retinal epithelium atrophy and externally oblique choroidal border tissue, circumpapillary retinal nerve fiber layer thickness (cpRNFLT), circumpapillary choroidal thickness (cpChT), lamina cribrosa parameters, and peripapillary scleral (PPS) angle were calculated from BMO-centered radial scans reconstructed from 3D raster scans. Multivariate linear mixed models were used to elucidate ONH parameters that are independently associated with AXL.

RESULTS

Longer AXL was associated with a greater misalignment between ASCO and BMO planes, larger region of externally oblique choroidal border tissue, thinner cpChT, larger PPS angle, larger ASCO area, and thicker cpRNFLT (all P < .040 after Bonferroni's correction for number of included explanatory variables).

CONCLUSIONS

A greater misalignment between BMO and ASCO planes, thinner choroid, a more posteriorly bowed PPS, an enlargement of ASCO, and thicker cpRNFLT were each associated with longer AXL. An enhanced understanding of these AXL-associated configurations should provide essential information to improve our ability to detect glaucoma-induced ONH morphology in myopic eyes.

Medical Application of Geometric Deep Learning for the Diagnosis of Glaucoma

Purpose

(1) To assess the performance of geometric deep learning in diagnosing glaucoma from a single optical coherence tomography (OCT) scan of the optic nerve head and (2) to compare its performance to that obtained with a three-dimensional (3D) convolutional neural network (CNN), and with a gold-standard parameter, namely, the retinal nerve fiber layer (RNFL) thickness.

Methods

Scans of the optic nerve head were acquired with OCT for 477 glaucoma and 2296 nonglaucoma subjects. All volumes were automatically segmented using deep learning to identify seven major neural and connective tissues. Each optic nerve head was then represented as a 3D point cloud with approximately 1000 points. Geometric deep learning (PointNet) was then used to provide a glaucoma diagnosis from a single 3D point cloud. The performance of our approach (reported using the area under the curve [AUC]) was compared with that obtained with a 3D CNN, and with the RNFL thickness.

Results

PointNet was able to provide a robust glaucoma diagnosis solely from a 3D point cloud (AUC = 0.95 ± 0.01).The performance of PointNet was superior to that obtained with a 3D CNN (AUC = 0.87 ± 0.02 [raw OCT images] and 0.91 ± 0.02 [segmented OCT images]) and with that obtained from RNFL thickness alone (AUC = 0.80 ± 0.03).

Conclusions

We provide a proof of principle for the application of geometric deep learning in glaucoma. Our technique requires significantly less information as input to perform better than a 3D CNN, and with an AUC superior to that obtained from RNFL thickness.

Translational Relevance

Geometric deep learning may help us to improve and simplify diagnosis and prognosis applications in glaucoma.

Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis

PURPOSE

To compare the performance of 2 relatively recent geometric deep learning techniques in diagnosing glaucoma from a single optical coherence tomographic (OCT) scan of the optic nerve head (ONH); and to identify the 3-dimensional (3D) structural features of the ONH that are critical for the diagnosis of glaucoma.

DESIGN

Comparison and evaluation of deep learning diagnostic algorithms.

METHODS

In this study, we included a total of 2247 nonglaucoma and 2259 glaucoma scans from 1725 participants. All participants had their ONHs imaged in 3D with Spectralis OCT. All OCT scans were automatically segmented using deep learning to identify major neural and connective tissues. Each ONH was then represented as a 3D point cloud. We used PointNet and dynamic graph convolutional neural network (DGCNN) to diagnose glaucoma from such 3D ONH point clouds and to identify the critical 3D structural features of the ONH for glaucoma diagnosis.

RESULTS

Both the DGCNN (area under the curve [AUC]: 0.97±0.01) and PointNet (AUC: 0.95±0.02) were able to accurately detect glaucoma from 3D ONH point clouds. The critical points (ie, critical structural features of the ONH) formed an hourglass pattern, with most of them located within the neuroretinal rim in the inferior and superior quadrant of the ONH.

CONCLUSIONS

The diagnostic accuracy of both geometric deep learning approaches was excellent. Moreover, we were able to identify the critical 3D structural features of the ONH for glaucoma diagnosis that tremendously improved the transparency and interpretability of our method. Consequently, our approach may have strong potential to be used in clinical applications for the diagnosis and prognosis of a wide range of ophthalmic disorders.

A Review of the Methods of Non-Invasive Assessment of Intracranial Pressure through Ocular Measurement

The monitoring of intracranial pressure (ICP) is essential for the detection and treatment of most craniocerebral diseases. Invasive methods are the most accurate approach to measure ICP; however, these methods are prone to complications and have a limited range of applications. Therefore, non-invasive ICP measurement is preferable in a range of scenarios. The current non-invasive ICP measurement methods comprise fluid dynamics, and ophthalmic, otic, electrophysiological, and other methods. This article reviews eight methods of non-invasive estimation of ICP from ocular measurements, namely optic nerve sheath diameter, flash visual evoked potentials, two-depth transorbital Doppler ultrasonography, central retinal venous pressure, optical coherence tomography, pupillometry, intraocular pressure measurement, and retinal arteriole and venule diameter ratio. We evaluated and presented the indications and main advantages and disadvantages of these methods. Although these methods cannot completely replace invasive measurement, for some specific situations and patients, non-invasive measurement of ICP still has great potential.

Glaucoma and biomechanics

PURPOSE OF REVIEW

Biomechanics is an important aspect of the complex family of diseases known as the glaucomas. Here, we review recent studies of biomechanics in glaucoma.

RECENT FINDINGS

Several tissues have direct and/or indirect biomechanical roles in various forms of glaucoma, including the trabecular meshwork, cornea, peripapillary sclera, optic nerve head/sheath, and iris. Multiple mechanosensory mechanisms and signaling pathways continue to be identified in both the trabecular meshwork and optic nerve head. Further, the recent literature describes a variety of approaches for investigating the role of tissue biomechanics as a risk factor for glaucoma, including pathological stiffening of the trabecular meshwork, peripapillary scleral structural changes, and remodeling of the optic nerve head. Finally, there have been advances in incorporating biomechanical information in glaucoma prognoses, including corneal biomechanical parameters and iridial mechanical properties in angle-closure glaucoma.

SUMMARY

Biomechanics remains an active aspect of glaucoma research, with activity in both basic science and clinical translation. However, the role of biomechanics in glaucoma remains incompletely understood. Therefore, further studies are indicated to identify novel therapeutic approaches that leverage biomechanics. Importantly, clinical translation of appropriate assays of tissue biomechanical properties in glaucoma is also needed.

Optical Coherence Tomography Imaging of the Lamina Cribrosa: Structural Biomarkers in Nonglaucomatous Diseases

The lamina cribrosa (LC) is an active structure that responds to the strain by changing its morphology. Abnormal changes in LC morphology are usually associated with, and indicative of, certain pathologies such as glaucoma, intraocular hypertension, and myopia. Recent developments in optical coherence tomography (OCT) have enabled detailed in vivo studies about the architectural characteristics of the LC. Structural characteristics of the LC have been widely explored in glaucoma management. However, information about which LC biomarkers could be useful for the diagnosis, and follow-up, of other diseases besides glaucoma is scarce. Hence, this literature review aims to summarize the role of the LC in nonophthalmic and ophthalmic diseases other than glaucoma. PubMed was used to perform a systematic review on the LC features that can be extracted from OCT images. All imaging features are presented and discussed in terms of their importance and applicability in clinical practice. A total of 56 studies were included in this review. Overall, LC depth (LCD) and thickness (LCT) have been the most studied features, appearing in 75% and 45% of the included studies, respectively. These biomarkers were followed by the prelaminar tissue thickness (21%), LC curvature index (5.4%), LC global shape index (3.6%), LC defects (3.6%), and LC strains/deformations (1.8%). Overall, the disease groups showed a thinner LC (smaller LCT) and a deeper ONH cup (larger LCD), with some exceptions. A large variability between approaches used to compute LC biomarkers has been observed, highlighting the importance of having automated and standardized methodologies in LC analysis. Moreover, further studies are needed to identify the pathologies where LC features have a diagnostic and/or prognostic value.