Profile and Determinants of Retinal Optical Intensity in Normal Eyes with Spectral Domain Optical Coherence Tomography

Assessment of Peripapillary Retinal Nerve Fiber Layer Optical Density Ratios in Healthy Eyes Using Optical Coherence Tomography with Different Analytical Radii

PURPOSE

To explore the characteristics and determinants of peripapillary retinal nerve fiber layer (RNFL) optical density (OD) by optical coherence tomography (OCT) in healthy eyes with varied analytical radii.

METHODS

Peripapillary OCT scans centered at the optic disc of 150 eyes from 150 healthy subjects (64 males and 86 females) were included. Under 5 analytical circles with different radii (1.45 mm, 1.7 mm, 1.95 mm, 2.2 mm and 2.45 mm), the circumpapillary circular cross-sectional images were exported for further analysis using Image J. Peripapillary RNFL and retinal pigment epithelium (RPE) OD in different quadrants and clock-hours were obtained. RNFL optical density ratio (ODR) was then calculated as RNFL OD divided by RPE OD. A linear mixed-effects model analysis was performed to assess the relationship between RNFL ODR and analytical radius, accounting for axial length, age, spherical equivalent, thickness and image score.

RESULTS

The RNFL ODRs had a double-hump pattern with peaks in the superior and inferior quadrants and troughs in the temporal and nasal areas. In the linear mixed-effects model analysis, a trend of decreasing mean RNFL ODR with increasing analytical radius was found (0.9227 ± 0.0689, 0.9063 ± 0.0620, 0.8916 ± 0.0552, 0.8729 ± 0.0553 and 0.8575 ± 0.0564 respectively, p = 0.034). RNFL ODR values was negatively correlated with age (p < 0.001), positively correlated with corresponding RNFL thickness (p < 0.001). No significant correlation was found between RFNL ODR and image score, axial length and spherical equivalent.

CONCLUSIONS

RNFL ODR profile showed a comparable double-hump configuration with RNFL thickness. RNFL ODR values tended to decrease with larger analytical circles and older age, and increase with corresponding RNFL thickness. These factors should be considered when interpreting RNFL ODR in glaucoma assessment.

Determinants of peripapillary retinal nerve fiber layer's grayscale value in normal eyes by spectral domain optical coherence tomography

To determine and evaluate the distribution, variation, and determinants of peripapillary retinal nerve fiber layer (pRNFL) grayscale value with spectral-domain optical coherence tomography (SD-OCT) in normal eyes. In this cross-sectional study, three hundred ninety-seven normal eyes from 397 healthy Chinese adults aged 18-80 were consecutively recruited from a tertiary eye care center. An SD-OCT instrument took pRNFL imaging. We used a customized software to measure pRNFL parameters, including thickness and grayscale value. Univariable and multiple linear regression analyses were performed to examine the relationship between pRNFL grayscale value with ocular (e.g., axial length [A.L.], spherical equivalent [S.E.], intraocular pressure [IOP]), and systemic (e.g., age, sex) factors. A total of 397 eyes from 397 healthy subjects were included in the final analysis with mean (± SD) age 44.63 ± 16.43 years (range 18-80 years) and 196 (49.4%) males. The mean average of pRNFL grayscale value and thickness 164.82 ± 5.69 and 106.68 ± 8.89 μm, respectively. pRNFL grayscale value in nasal sectors (163.26 ± 9.31) was significantly lower comparing those in all other five sectors (all with p < 0.001)]. In multivariable analysis, average pRNFL grayscale value was independently correlated to older age (β = - 0.053, p = 0.002), longer axial length (β = - 0.664, p = 0.003), lower RPE grayscale value (β = 0.372, p < 0.001) and lower ImageQ (β = 0.658, p < 0.001). In this study, we provided normative SD-OCT data on the pRNFL grayscale value profile in nonglaucomatous eyes. Lower average pRNFL grayscale value was independently correlated to older age, longer axial length, lower RPE grayscale value, and lower ImageQ. These determinants should be considered when interpreting pRNFL grayscale value in glaucoma assessment.

Depth-resolved variations in visibility of retinal nerve fibre bundles across the retina in enface OCT images of healthy eyes

PURPOSE

Recent developments in optical coherence tomography (OCT) technology enable direct enface visualisation of retinal nerve fibre bundle (RNFB) loss in glaucoma. However, the optimum depth at which to visualise RNFBs across the retina is unknown. We aimed to evaluate the range of depths and optimum depth at which RNFBs can be visualised across the retina in healthy eyes.

METHODS

The central ± 25° retina of 10 healthy eyes from 10 people aged 57-75 years (median 68.5 years) were imaged with spectral domain OCT. Slab images of maximum axial resolution (4 μm) containing depth-resolved attenuation coefficients were extracted from 0 to 193.5 μm below the inner limiting membrane (ILM). Bundle visibility within 10 regions of a superimposed grid was assessed subjectively by trained optometrists (n = 8), according to written instructions. Anterior and posterior limits of RNFB visibility and depth of best visibility were identified for each grid sector. Effects of retinal location and individual eye on RNFB visibility were explored using linear mixed modelling with likelihood ratio tests. Intraclass correlation coefficient (ICC) was used to measure overall agreement and repeatability of grading. Spearman's correlation was used to measure correlation between depth range of visible RNFBs and retinal nerve fibre layer thickness (RNFLT).

RESULTS

Retinal location and individual eye affected anterior limit of visibility (χ² ₍₉₎  = 58.6 and 60.5, both p < 0.0001), but none of the differences exceeded instrument resolution, making anterior limit consistent across the retina and different eyes. Greater differences were observed in the posterior limit of visibility across retinal areas (χ² ₍₉₎  = 1671.1, p < 0.0001) and different eyes (χ² ₍₉₎  = 88.7, p < 0.0001). Optimal depth for visualisation of RNFBs was around 20 µm below the ILM in most regions. It varied slightly with retinal location (χ² ₍₉₎  = 58.8, p < 0.0001), but it was not affected by individual eye (χ² ₍₉₎  = 10.7, p = 0.29). RNFB visibility showed good agreement between graders (ICC 0.89, 95%CI 0.87-0.91), and excellent repeatability (ICC 0.96-0.99). Depth range of visible RNFBs was highly correlated with RNFLT (ρ = 0.9, 95%CI: 0.86-0.95).

CONCLUSIONS

The range of depths with visible RNFBs varies markedly across the healthy retina, consistently with RNFLT. To extract all RNFB information consistently across the retina, slab properties should account for differences across retinal locations and between individual eyes.

A Reflectivity Measure to Quantify Bruch's Membrane Calcification in Patients with Pseudoxanthoma Elasticum Using Optical Coherence Tomography

Purpose

Progressive calcification of Bruch's membrane (BM) causes considerable visual morbidity in patients with pseudoxanthoma elasticum (PXE). Since calcification is hyperreflective on optical coherence tomography (OCT), our aim was to measure BM calcification with OCT imaging.

Methods

Case-control study with 45 patients with PXE under 40 years (range, 11-39) and 25 controls (range, 14-39). Spectralis HRA-OCT imaging consisted of seven macular B-scans with 250-µm spacing. Retinal segmentation was performed with the IOWA Reference Algorithms. MATLAB was used to extract and average z-axis reflectivity profiles. Layer reflectivities were normalized to the ganglion cell and inner plexiform layers. Both median and peak layer reflectivities were compared between patients with PXE and controls. The discriminative value of the retinal pigment epithelium (RPE)-BM peak reflectivity was analyzed using receiver operating characteristic analysis.

Results

The reflectivity profile of patients with PXE differed from controls in the outer retinal layers. The normalized median RPE-BM reflectivity was 41.1 (interquartile range [IQR], 26.3-51.9) in patients with PXE, compared with 22.5 (IQR, 19.3-29.5) in controls (P = 2.09 × 10^-3). The normalized RPE-BM peak reflectivity was higher in patients with PXE (67.5; IQR, 42.1-84.2) than in controls (32.7; IQR, 25.7-38.9; P = 2.43 × 10^-5) and had a high discriminative value with an area under the curve of 0.85 (95% confidence interval, 0.76-0.95). In patients with PXE under 40 years, increasing age did not have a statistically significant effect on the RPE-BM peak reflectivity (patients under 20 years: 44.2 [IQR, 40.5-74.6]; 20-30 years: 66.0 [IQR, 45.1-83.8]; 30-40 years: 70.8 [IQR, 49.0-88.0], P = 0.47).

Conclusions

BM calcification can be measured as increased RPE-BM reflectivity in young patients with PXE and has a high discriminative value.

Translational Relevance

In patients with PXE, the OCT reflectivity of Bruch's membrane may be the first biomarker for Bruch's membrane calcification and a valuable ophthalmologic endpoint in clinical trials.

Detecting glaucoma based on spectral domain optical coherence tomography imaging of peripapillary retinal nerve fiber layer: a comparison study between hand-crafted features and deep learning model

PURPOSE

To develop a deep learning (DL) model for automated detection of glaucoma and to compare diagnostic capability against hand-craft features (HCFs) based on spectral domain optical coherence tomography (SD-OCT) peripapillary retinal nerve fiber layer (pRNFL) images.

METHODS

A DL model with pre-trained convolutional neural network (CNN) based was trained using a retrospective training set of 1501 pRNFL OCT images, which included 690 images from 153 glaucoma patients and 811 images from 394 normal subjects. The DL model was further tested in an independent test set of 50 images from 50 glaucoma patients and 52 images from 52 normal subjects. A customized software was used to extract and measure HCFs including pRNFL thickness in average and four different sectors. Area under the receiver operator characteristics (AROC) curves was calculated to compare the diagnostic capability between DL model and hand-crafted pRNFL parameters.

RESULTS

In this study, the DL model achieved an AROC of 0.99 [CI: 0.97 to 1.00] which was significantly larger than the AROC values of all other HCFs (AROCs 0.661 with 95% CI 0.549 to 0.772 for temporal sector, AROCs 0.696 with 95% CI 0.549 to 0.799 for nasal sector, AROCs 0.913 with 95% CI 0.855 to 0.970 for superior sector, AROCs 0.938 with 95% CI 0.894 to 0.982 for inferior sector, and AROCs 0.895 with 95% CI 0.832 to 0.957 for average).

CONCLUSION

Our study demonstrated that DL models based on pre-trained CNN are capable of identifying glaucoma with high sensitivity and specificity based on SD-OCT pRNFL images.

A computational framework to investigate retinal haemodynamics and tissue stress

The process of vision begins in the retina, yet the role of biomechanical forces in the retina is relatively unknown and only recently being explored. This contribution describes a computational framework involving 3D fluid-structure interaction simulations derived from fundus images that work towards creating unique data on retinal biomechanics. We developed methods to convert 2D fundus photographs into 3D geometries that follow the curvature of the retina. Retina arterioles are embedded into a six-layer representation of the retinal tissue with varying material properties throughout the retinal tissue. Using three different human retinas (healthy, glaucoma, diabetic retinopathy) and by varying our simulation approaches, we report the effects of transient versus steady flow, viscosity assumptions (Newtonian, non-Newtonian and Fåhræus-Lindqvist effect) and rigid versus compliant retinal tissue, on resulting wall shear stress (WSS) and von Mises stress. In the retinal arterioles, the choice of viscosity model is important and WSS obtained from models with the Fåhræus-Lindqvist effect is markedly different from Newtonian and non-Newtonian models. We found little difference in WSS between steady-state and pulsatile simulations (< 5%) and show that WSS varies by about 7% between rigid and deformable models. Comparing the three geometries, we found notably different WSS in the healthy (3.3 ± 1.3 Pa), glaucoma (5.7 ± 1.6 Pa) and diabetic retinopathy cases (4.3 ± 1.1 Pa). Conversely, von Mises stress was similar in each case. We have reported a novel biomechanical framework to explore the stresses in the retina. Despite current limitations and lack of complete subject-specific physiological inputs, we believe our framework is the first of its kind and with further improvements could be useful to better understand the biomechanics of the retina.

OIPAV: an Integrated Software System for Ophthalmic Image Processing, Analysis, and Visualization

Ophthalmic medical images, such as optical coherence tomography (OCT) images and color photo of fundus, provide valuable information for clinical diagnosis and treatment of ophthalmic diseases. In this paper, we introduce a software system specially oriented to ophthalmic images processing, analysis, and visualization (OIPAV) to assist users. OIPAV is a cross-platform system built on a set of powerful and widely used toolkit libraries. Based on the plugin mechanism, the system has an extensible framework. It provides rich functionalities including data I/O, image processing, interaction, ophthalmic diseases detection, data analysis, and visualization. By using OIPAV, users can easily access to the ophthalmic image data manufactured from different imaging devices, facilitate workflows of processing ophthalmic images, and improve quantitative evaluations. With a satisfying function scalability and expandability, the software is applicable for both ophthalmic researchers and clinicians.