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

Comparing the morphology of optic nerve head and lamina cribrosa in full-term and preterm school-aged children

OBJECTIVES

To evaluate the morphology of lamina cribrosa (LC) in preterm school-aged children.

METHODS

A study of 120 eyes from 120 patients, including 42 full-term children (control group), 41 preterm children without retinopathy of prematurity (ROP), 16 children with ROP treated with intravitreal bevacizumab (IVB), and 21 children with ROP treated with laser. Five parameters of LC were measured by optical coherence tomography, including Bruch's membrane opening (BMO) diameter, minimum rim width (MRW), LC depth, prelaminar tissue (PLT) thickness, and LC curvature index (LCCI).

RESULTS

The PLT thickness increased with age in full-term and preterm children (β = 30.1, P = 0.003 and β = 19.6, P < 0.001, respectively). LC depth and LCCI showed no differences between full-term and preterm children. Worse refractive errors in preterm children were associated with greater MRW and PLT thickness (β = -17.1, P = 0.001 and β = -5.7, P = 0.03, respectively). However, this relationship was not found in full-term children. Laser-treated children had greater MRW, PLT, temporal peripapillary retinal nerve fibre layer, and foveal thickness than full-term or other preterm children (all P < 0.05).

CONCLUSIONS

Prematurity and ROP treatment may have an impact on the structural development of the LC. Refractive status plays a vital role in the LC structure of preterm children. This highlights the refractive errors of preterm children at school age that merit greater attention.

Analysis of volumetric 3D reconstruction of lamina cribrosa images from swept-source optical coherence tomography in glaucomatous and healthy subjects

This study demonstrates the 3D visualization of the lamina cribrosa (LC) structure and its correlation with volumetric data, pore volume, and disc area in glaucomatous and non-glaucomatous eyes. The participant cohort included 65 glaucomatous and 58 non-glaucomatous eyes (13 suspected glaucoma and 45 normal). An ophthalmologist diagnosed glaucoma patients and all subjects were over 18 years old, passed a visual field test, and underwent optical coherence tomography (OCT) examinations. LC images were obtained using the DRI OCT Triton, while optic disc images were obtained from the enface image of the Cirrus HD-OCT 5000. Since LC images alone did not provide clear edge information, we used optic disc images as a reference for edge detection. To achieve this, we employed a fine-tuned model, specifically a pre-trained U-shaped Encoder-Decoder Network with Attention. This model was used to obtain a segmented mask, which was then aligned and utilized to locate the edge of the LC in the LC images. A blood vessel mask was created to remove blood vessels, as they can interfere with the accurate visualization and analysis of LC characteristics. This step allowed for the 3D reconstruction of the LC structure without the presence of blood vessels. Correlations between LC volume, pore volume, and pore volume to LC volume were calculated separately for glaucomatous and non-glaucomatous eyes. We divided the areas for considering the LC structure into three types: overall, quadrants, and 12-clock-hour sectors. Based on the experimental results, we found that the pore volume and pore-to-LC volume were different between glaucoma and normal across all areas considered. In conclusion, this research generated 3D images of the LC from OCT images using computer techniques, showcasing a microstructure that closely resembles the actual LC. Statistical methods were employed to calculate and analyze the differences observed between the two groups of samples.

Optical coherence tomography and optical coherence tomography — angiography used in endocrine ophthalmopathy

The literature review presents the results of optical coherence tomography and optical coherence tomography — angiography used for Graves’ orbitopathy. The data on the thickness of the inner layers of the retina, microcirculation in the peripapillary and macular regions, parameters of the choroid, lamina cribrosa and extraocular muscles were analyzed as possible diagnostic criteria of the condition.

Automatic Segmentation of the Optic Nerve Head Region in Optical Coherence Tomography: A Methodological Review

The optic nerve head (ONH) represents the intraocular section of the optic nerve, which is prone to damage by intraocular pressure (IOP). The advent of optical coherence tomography (OCT) has enabled the evaluation of novel ONH parameters, namely the depth and curvature of the lamina cribrosa (LC). Together with the Bruch's membrane minimum-rim-width (BMO-MRW), these seem to be promising ONH parameters for diagnosis and monitoring of retinal diseases such as glaucoma. Nonetheless, these OCT derived biomarkers are mostly extracted through manual segmentation, which is time-consuming and prone to bias, thus limiting their usability in clinical practice. The automatic segmentation of ONH in OCT scans could further improve the current clinical management of glaucoma and other diseases. This review summarizes the current state-of-the-art in automatic segmentation of the ONH in OCT. PubMed and Scopus were used to perform a systematic review. Additional works from other databases (IEEE, Google Scholar and ARVO IOVS) were also included, resulting in a total of 29 reviewed studies. For each algorithm, the methods, the size and type of dataset used for validation, and the respective results were carefully analysed. The results show a lack of consensus regarding the definition of segmented regions, extracted parameters and validation approaches, highlighting the importance and need of standardized methodologies for ONH segmentation. Only with a concrete set of guidelines, these automatic segmentation algorithms will build trust in data-driven segmentation models and be able to enter clinical practice.

Are There Static-Structural Biomarkers for Glaucoma with OCT?

Glaucomas lead to uniform, specific and slowly developing atrophy of the optic nerve with progressing visual field defects in late stages. Early diagnosis is challenging, but necessary as optic nerve damage is irreparable. Biomarkers with structural optical coherence tomography (OCT) flag optic atrophy but do not prove to be specific in the differential diagnosis to other forms of optic atrophy. Combination of OCT parameters and their correlation to other variables facilitate glaucoma diagnosis. Use of artificial intelligence (AI) in structural OCT images may prove to be superior and as biomarker more specific to thickness measurements of neuronal tissues alone.