Cone photoreceptor definition on adaptive optics retinal imaging

Modeling Human Macular Cone Photoreceptor Spatial Distribution

Purpose

The purpose of this study was to investigate the spatial distribution of human cone photoreceptors and examine cone density differences between the retinal meridians and quadrants.

Method

Using adaptive optics scanning laser ophthalmoscopy, the maculae were imaged in 17 eyes of 11 subjects with normal chorioretinal health aged 54 to 72 years. We measured cone density at 325 points within the central 10 degrees radius of the retina. Cone density spatial distributions along the primary retinal meridians and in four macular quadrants (superior-nasal, superior-temporal, inferior-temporal, and inferior-nasal) were analytically modeled using the polynomial function to assess the meridional and quadrantal difference.

Results

The mean and 95% confidence interval for the prediction of cone density along the primary retinal meridians was modeled with a 7-degree one-variable polynomial (R2 = 0.9761, root mean squared error [RMSE] = 0.0585). In the 4 retinal quadrants, cone density distribution was described by a 2-variable polynomial with X degree 3 and Y degree 4 (R² = 0.9834, RMSE = 0.0377). The models suggest no statistically significant difference between medians and between quadrants. However, cone density difference at corresponding spatial locations in different areas can be up to 25.6%. The superior-nasal region has more areas with high cone density, followed by quadrants of inferior-nasal, inferior-temporal, and superior-temporal.

Conclusions

Analytical modeling provides comprehensive knowledge of cone distribution across the entire macula. Although modeling analysis suggests no statistically significant difference between medians and between quadrants, the remarkable cone density discrepancies in certain regions should be accounted for in applications requiring sensitive detection of cone variation.

Progression of Rare Inherited Retinal Dystrophies May Be Monitored by Adaptive Optics Imaging

Inherited retinal dystrophies (IRDs) are bilateral genetic conditions of the retina, leading to irreversible vision loss. This study included 55 eyes afflicted with IRDs affecting the macula. The diseases examined encompassed Stargardt disease (STGD), cone dystrophy (CD), and cone-rod dystrophy (CRD) using adaptive optics (Rtx1™; Imagine Eyes, Orsay, France). Adaptive optics facilitate high-quality visualisation of retinal microstructures, including cones. Cone parameters, such as cone density (DM), cone spacing (SM), and regularity (REG), were analysed. The best corrected visual acuity (BCVA) was assessed as well. Examinations were performed twice over a 6-year observation period. A significant change was observed in DM (1282.73/mm2 vs. 10,073.42/mm2, p< 0.001) and SM (9.83 μm vs. 12.16 μm, p< 0.001) during the follow-up. BCVA deterioration was also significant (0.16 vs. 0.12, p = 0.001), albeit uncorrelated with the change in cone parameters. No significant difference in REG was detected between the initial examination and the follow-up (p = 0.089).

Characteristics of Rare Inherited Retinal Dystrophies in Adaptive Optics-A Study on 53 Eyes

Inherited retinal dystrophies (IRDs) are genetic disorders that lead to the bilateral degeneration of the retina, causing irreversible vision loss. These conditions often manifest during the first and second decades of life, and their primary symptoms can be non-specific. Diagnostic processes encompass assessments of best-corrected visual acuity, fundoscopy, optical coherence tomography, fundus autofluorescence, fluorescein angiography, electrophysiological tests, and genetic testing. This study focuses on the application of adaptive optics (AO), a non-invasive retinal examination, for the assessment of patients with IRDs. AO facilitates the high-quality, detailed observation of retinal photoreceptor structures (cones and rods) and enables the quantitative analysis of parameters such as cone density (DM), cone spacing (SM), cone regularity (REG), and Voronoi analysis (N%6). AO examinations were conducted on eyes diagnosed with Stargardt disease (STGD, N=36), cone dystrophy (CD, N=9), and cone-rod dystrophy (CRD, N=8), and on healthy eyes (N=14). There were significant differences in the DM, SM, REG, and N%6 parameters between the healthy and IRD-affected eyes (p<0.001 for DM, SM, and REG; p=0.008 for N%6). The mean DM in the CD, CRD, and STGD groups was 8900.39/mm2, 9296.32/mm2, and 16,209.66/mm2, respectively, with a significant inter-group difference (p=0.006). The mean SM in the CD, CRD, and STGD groups was 12.37 μm, 14.82 μm, and 9.65 μm, respectively, with a significant difference observed between groups (p=0.002). However, no significant difference was found in REG and N%6 among the CD, CRD, and STGD groups. Significant differences were found in SM and DM between CD and STGD (p=0.014 for SM; p=0.003 for DM) and between CRD and STGD (p=0.027 for SM; p=0.003 for DM). Our findings suggest that AO holds significant potential as an impactful diagnostic tool for IRDs.

Pearls and Pitfalls of Adaptive Optics Ophthalmoscopy in Inherited Retinal Diseases

Adaptive optics (AO) retinal imaging enables individual photoreceptors to be visualized in the clinical setting. AO imaging can be a powerful clinical tool for detecting photoreceptor degeneration at a cellular level that might be overlooked through conventional structural assessments, such as spectral-domain optical coherence tomography (SD-OCT). Therefore, AO imaging has gained significant interest in the study of photoreceptor degeneration, one of the most common causes of inherited blindness. Growing evidence supports that AO imaging may be useful for diagnosing early-stage retinal dystrophy before it becomes apparent on fundus examination or conventional retinal imaging. In addition, serial AO imaging may detect structural disease progression in early-stage disease over a shorter period compared to SD-OCT. Although AO imaging is gaining popularity as a structural endpoint in clinical trials, the results should be interpreted with caution due to several pitfalls, including the lack of standardized imaging and image analysis protocols, frequent ocular comorbidities that affect image quality, and significant interindividual variation of normal values. Herein, we summarize the current state-of-the-art AO imaging and review its potential applications, limitations, and pitfalls in patients with inherited retinal diseases.

Volume-accumulated reflectivity of the outer retina (integral) on spectral domain optical coherence tomography as a predictor of cone cell density: a pilot study

BACKGROUND

The study aims to investigate the relationship between the volume-accumulated reflectivity (termed "integral") on spectral domain optical coherence tomography (SD-OCT) and cone density on adaptive optics (AO) imaging.

METHODS

In this cross-sectional study, both eyes of 32 healthy subjects and 5 patients with inherited retinal diseases (IRD) were studied. The parameter, integral, was defined as the volume-accumulated reflectivity values in a selected region on OCT images; integrals of the ellipsoid zone (EZ) and interdigitation zone (IZ) were measured at 2°, 3°, 4°, 5°and 6° eccentricity along the four meridians on fovea-centered OCT B-scans. Cone density in the same region was measured using a flood illumination adaptive optics camera RTX1.

RESULTS

Integrals of EZ, IZ and cone density shared similar distribution patterns. Integral of the IZ was better correlated with cone density in both healthy people (r = 0.968, p < 0.001) and those with IRD (r = 0.823, p < 0.001) than direct measurements of reflectivity on OCT images. A strong correlation was found between best corrected visual acuity (BCVA) and cone density at 2° eccentricity (r = -0.857, p = 0.002). BCVA was also correlated with the integral of the IZ at the foveola (r = -0.746, p = 0.013) and fovea (r = -0.822, p = 0.004).

CONCLUSIONS

The new parameter "integral" of the photoreceptor outer segment measured from SD-OCT was noted to correlate with cone density and visual function in this pilot study.

Comprehensive automatic processing and analysis of adaptive optics flood illumination retinal images on healthy subjects

This work presents a novel fully automated method for retinal analysis in images acquired with a flood illuminated adaptive optics retinal camera (AO-FIO). The proposed processing pipeline consists of several steps: First, we register single AO-FIO images in a montage image capturing a larger retinal area. The registration is performed by combination of phase correlation and the scale-invariant feature transform method. A set of 200 AO-FIO images from 10 healthy subjects (10 images from left eye and 10 images from right eye) is processed into 20 montage images and mutually aligned according to the automatically detected fovea center. As a second step, the photoreceptors in the montage images are detected using a method based on regional maxima localization, where the detector parameters were determined with Bayesian optimization according to manually labeled photoreceptors by three evaluators. The detection assessment, based on Dice coefficient, ranges from 0.72 to 0.8. In the next step, the corresponding density maps are generated for each of the montage images. As a final step, representative averaged photoreceptor density maps are created for the left and right eye and thus enabling comprehensive analysis across the montage images and a straightforward comparison with available histological data and other published studies. Our proposed method and software thus enable us to generate AO-based photoreceptor density maps for all measured locations fully automatically, and thus it is suitable for large studies, as those are in pressing need for automated approaches. In addition, the application MATADOR (MATlab ADaptive Optics Retinal Image Analysis) that implements the described pipeline and the dataset with photoreceptor labels are made publicly available.

Comparison of Cone Mosaic Metrics From Images Acquired With the SPECTRALIS High Magnification Module and Adaptive Optics Scanning Light Ophthalmoscopy

Purpose

To compare cone mosaic metrics derived from adaptive optics scanning light ophthalmoscopy (AOSLO) images with those derived from Heidelberg Engineering SPECTRALIS High Magnification Module (HMM) images.

Methods

Participants with contiguous cone mosaics had HMM imaging performed at locations superior and temporal to the fovea. These images were registered and averaged offline and then aligned to split-detection AOSLO images; 200 × 200-µm regions of interest were extracted from both modalities. Cones were semi-automatically identified by two graders to provide estimates of cone density and spacing.

Results

Thirty participants with contiguous cone mosaics were imaged (10 males, 20 females; age range, 11-67 years). Image quality varied, and 80% of our participants had analyzable HMM images. The intergrader intraclass correlation coefficients for cone metrics were good for both modalities (0.688-0.757 for HMM; 0.805-0.836 for AOSLO). Cone density estimates from HMM images were lower by 2661 cones/mm2 (24.1%) on average compared to AOSLO-derived estimates. Accordingly, HMM estimates of cone spacing were increased on average compared to AOSLO.

Conclusions

The cone mosaic can be visualized in vivo using the SPECTRALIS HMM, although image quality is variable and imaging is not successful in every individual. Metrics extracted from HMM images can differ from those from AOSLO, although excellent agreement is possible in individuals with excellent optical quality and precise co-registration between modalities.

Translational Relevance

Emerging non-adaptive optics-based photoreceptor imaging is more clinically accessible than adaptive optics techniques and has potential to expand high-resolution imaging in a clinical environment.

Chromatic Full-Field Stimulus Thresholds in Patients with Treatment-Naive Age-Related Macular Degeneration

Purpose

To evaluate retinal sensitivity using chromatic full-field stimulus thresholds (FST) in patients with treatment naive exudative age-related macular degeneration (e-ARMD) before and during the first intravitreal anti-vascular endothelial growth factor (anti-VEGF) treatment.

Patients and Methods

After general ophthalmological examinations to diagnose patients with e-ARMD the FST, the central foveal thickness (FCt) and the visual acuity were assessed in 20 eyes of 20 patients during this prospective study. Examinations were performed before and during the first treatment series with three intravitreal anti-VEGF injections. Normal values for FST were assessed in 19 eyes of 19 healthy subjects. Results were analyzed using Student’s two-tailed t-test and Pearson’s correlation coefficients between all functional parameters.

Results

At baseline and before the 1st intravitreal anti-VEGF treatment, a moderately significant negative correlation between VA and FCt was found in the e-ARMD group (p = 0.02, r = −0.45 and p = 0.03, r = −0.45), respectively. After the 2nd intravitreal anti-VEGF injection, no significant correlation between VA and FCt was found (p = 0.12). However, a significant correlation between FCt and blue FST was evident (p = 0.04, r = 0.4). After the 3rd intravitreal anti-VEGF treatment, there was no correlation evident between VA and FCt (p = 0.31) but a high significant correlation between FCt and FST using red (p = 0.01, r = 0.53), green (p = 0.002, r = 0.6) and blue light (p = 0.007, r = 0.66).

Conclusion

During anti-VEGF treatment in patients with e-ARMD, the FST test showed higher significant correlations with the morphology measured by FCt, as it is the case for VA. These findings support that the FST test might serve as a valuable diagnostic tool for monitoring patients with e-ARMD and enhance functional assessment of retinal function under treatment with anti-VEGF.

Short-Term Parafoveal Cone Loss Despite Preserved Ellipsoid Zone in Rod Cone Dystrophy

Purpose

Rod–cone dystrophy (RCD) is characterized by centripetal loss of rod followed by cone photoreceptors. In this prospective, observational cohort, we used flood-illumination adaptive optics (AO) imaging to investigate parafoveal cone loss in regions with preserved ellipsoid zone (EZ) in patients with RCD.

Methods

Eight patients with RCD and 10 age-matched healthy controls underwent spectral-domain optical coherence tomography and AO imaging. The RCD cohort underwent a follow-up examination after 6 months. Cone density (CD) and intercone distance (ICD) measurements were performed at 2° temporal from the fovea. Baseline CD and ICD values were compared between the control and patient groups, and longitudinal changes were calculated in the patient group. Residual EZ span in patients was measured in horizontal foveal B-scans.

Results

Between the control and patient groups, there was no significant difference in the baseline CD (2094 vs. 1750 cells/deg², respectively; P = 0.09) and ICD (1.46 vs. 1.62 arcmin, respectively; P = 0.08). Mean CD declined by 198 cells/deg² (−11.3%; P < 0.01), and mean ICD increased by 0.09 arcmin (+5.6%; P = 0.01) at the 6-month follow-up in the patient group. Mean baseline and follow-up residual EZ spans in the six patients with EZ defect were 3189 µm and 3065 µm, respectively (−3.9%; P = 0.08).

Conclusions

AO imaging detected significant parafoveal cone loss over 6-month follow-up even in regions with preserved EZ. Further studies to refine AO imaging protocol and validate cone metrics as a structural endpoint in early RCD are warranted.

Translational Relevance

CD and ICD may change prior to EZ span shortening in RCD.

Evaluation of focus and deep learning methods for automated image grading and factors influencing image quality in adaptive optics ophthalmoscopy

Adaptive optics flood illumination ophthalmoscopy (AO-FIO) is an established imaging tool in the investigation of retinal diseases. However, the clinical interpretation of AO-FIO images can be challenging due to varied image quality. Therefore, image quality assessment is essential before interpretation. An image assessment tool will also assist further work on improving the image quality, either during acquisition or post processing. In this paper, we describe, validate and compare two automated image quality assessment methods; the energy of Laplacian focus operator (LAPE; not commonly used but easily implemented) and convolutional neural network (CNN; effective but more complex approach). We also evaluate the effects of subject age, axial length, refractive error, fixation stability, disease status and retinal location on AO-FIO image quality. Based on analysis of 10,250 images of 50 × 50 μm size, at 41 retinal locations, from 50 subjects we demonstrate that CNN slightly outperforms LAPE in image quality assessment. CNN achieves accuracy of 89%, whereas LAPE metric achieves 73% and 80% (for a linear regression and random forest multiclass classifier methods, respectively) compared to ground truth. Furthermore, the retinal location, age and disease are factors that can influence the likelihood of poor image quality.

Computer-assisted photoreceptor assessment on Heidelberg Engineering Spectralis™ High Magnification Module™ images

Purpose

To evaluate reliability and repeatability of computer-assisted measurements of cone photoreceptor metrics on Heidelberg Engineering Spectralis™ High Magnification Module (HMM™) Automatic Real-time Tracking (ART™) images.

Methods

We analyzed HMM™ images in three separate study arms. Computer-assisted cone identification software was validated using an open-access adaptive optics (AO) dataset. We compared results of the first arm to data from AO and histology. We evaluated intersession repeatability of our computer-assisted cone analysis in the second arm. We assessed the capability of HMM™ to visualize cones in the presence of pathology in the third arm.

Results

We included 10 healthy subjects in the first arm of our study, 5 additional healthy participants in the second arm and 5 patients in the third arm. In total, we analyzed 225 regions of interest on HMM™ images. We were able to automatically identify cone photoreceptors and assess corresponding metrics at all eccentricities between 2 and 9° from the fovea. Cone density significantly declined with increasing eccentricity (p = 4.890E-26, Friedman test). With increasing eccentricity, we found a significant increase in intercell distance (p = 2.196E-25, Friedman test) and nearest neighbor distance (p = 1.997E-25, Friedman test). Cone hexagonality ranged between 71 and 85%. We found excellent automated intersession repeatability of cone density counts and spacing measurements. In pathology, we were also able to repeatedly visualize photoreceptors.

Conclusion

Computer-assisted cone photoreceptor analysis on Spectralis™ HMM™ images is feasible, and most cone metrics show excellent repeatability. HMM™ imaging may be useful for photoreceptor analysis as progression marker in outer retinal disease.

Promises and pitfalls of evaluating photoreceptor-based retinal disease with adaptive optics scanning light ophthalmoscopy (AOSLO)

Adaptive optics scanning light ophthalmoscopy (AOSLO) allows visualization of the living human retina with exquisite single-cell resolution. This technology has improved our understanding of normal retinal structure and revealed pathophysiological details of a number of retinal diseases. Despite the remarkable capabilities of AOSLO, it has not seen the widespread commercial adoption and mainstream clinical success of other modalities developed in a similar time frame. Nevertheless, continued advancements in AOSLO hardware and software have expanded use to a broader range of patients. Current devices enable imaging of a number of different retinal cell types, with recent improvements in stimulus and detection schemes enabling monitoring of retinal function, microscopic structural changes, and even subcellular activity. This has positioned AOSLO for use in clinical trials, primarily as exploratory outcome measures or biomarkers that can be used to monitor disease progression or therapeutic response. AOSLO metrics could facilitate patient selection for such trials, to refine inclusion criteria or to guide the choice of therapy, depending on the presence, absence, or functional viability of specific cell types. Here we explore the potential of AOSLO retinal imaging by reviewing clinical applications as well as some of the pitfalls and barriers to more widespread clinical adoption.

Retinal Differential Light Sensitivity Variation Across the Macula in Healthy Subjects: Importance of Cone Separation and Loci Eccentricity

Purpose

Microperimetry measures differential light sensitivity (DLS) at specific retinal locations. The aim of this study is to examine the variation in DLS across the macula and the contribution to this variation of cone distribution metrics and retinal eccentricity.

Methods

Forty healthy eyes of 40 subjects were examined by microperimetry (MAIA) and adaptive optics imaging (rtx1). Retinal DLS was measured using the grid patterns: foveal (2°–3°), macular (3°–7°), and meridional (2°–8° on horizontal and vertical meridians). Cone density (CD), distribution regularity, and intercone distance (ICD) were calculated at the respective test loci coordinates. Linear mixed-effects regression was used to examine the association between cone distribution metrics and loci eccentricity, and retinal DLS.

Results

An eccentricity-dependent reduction in DLS was observed on all MAIA grids, which was greatest at the foveal-parafoveal junction (2°–3°) (−0.58 dB per degree, 95% confidence interval [CI]; −0.91 to −0.24 dB, P < 0.01). Retinal DLS across the meridional grid changed significantly with each 1000 cells/deg² change in CD (0.85 dB, 95% CI; 0.10 to 1.61 dB, P = 0.03), but not with each arcmin change in ICD (1.36 dB, 95% CI; −2.93 to 0.20 dB, P = 0.09).

Conclusions

We demonstrate significant variation in DLS across the macula. Topographical change in cone separation is an important determinant of the variation in DLS at the foveal-parafoveal junction. We caution the extrapolation of changes in DLS measurements to cone distribution because the relationship between these variables is complex.

Translational Relevance

Cone density is an independent determinant of DLS in the foveal-parafoveal junction in healthy eyes.

Cone parameters in different vision levels from the adaptive optics imaging

To investigate the relationship between visual resolution and cone parameters in eyes with different levels of best corrected visual acuity (BCVA).Seventeen eyes of 10 volunteers with BCVA of 20/12.5 or better (group 1) and 16 eyes of 10 volunteers with BCVA of 20/16 (group 2) were investigated in the study. Images of the cone photoreceptors at 1.5° from the fovea were obtained using an adaptive optics (AO) retinal camera. The BCVA was obtained following a subjective refraction using a standardized logMAR visual acuity chart.The mean cone density (29,570.96 ± 2489.94 cells/mm2) at 1.5° from the fovea in group 1 (BCVA ≥ 20/12.5, n = 17) was significantly greater (P < .001) than that (22,963.59 ± 2987.92 cells/mm2) in group 2 (BCVA = 20/16, n = 16). The cone spacing at 1.5° from the fovea in group 1 was 6.45 ± 0.28 μm (mean ± SD), which was significantly smaller (P < .001) than 7.36 ± 0.50 μm (mean ± SD) in group 2. In the stepwise regression analysis, greater angular cone density (odds ratio [OR], 4.48; P = .005) and smaller angular cone spacing (OR, 0.60; P = .007) at 1.5° from the fovea were significantly associated with the better BCVA.The greater cone density and smaller cone spacing at the parafovea were found in eyes with BCVA of 20/12.5 or better, as compared to that in eyes with BCVA of 20/16. Knowledge of cone distribution for different BCVA levels may be beneficial for different clinical conditions.

Adaptive Optics Imaging in Patients Affected by Pseudoxanthoma Elasticum

PURPOSE

To describe the retinal findings of patients affected by pseudoxanthoma elasticum (PXE) using a multimodal imaging approach including flood-illumination adaptive optics ophthalmoscopy (AO).

DESIGN

Retrospective case series.

MATERIALS AND METHODS

Patients affected by PXE were retrospectively studied. Clinical data, color, infrared and autofluorescence fundus imaging, optical coherence tomographic scans, and AO examinations were collected. Furthermore, the photoreceptor count was assessed. PXE diagnosis was confirmed by a positive skin biopsy and/or genetic testing.

RESULTS

Twenty-one eyes of 18 patients (11 females and 7 males) were included in the study. In 3 patients, both eyes were studied. The mean age at examination was 37.7 ± 16.4 years (range 14-66) and the mean best-corrected visual acuity (BCVA) was 0.1 ± 0.2 logMAR (range 0-1). We identified 3 types of angioid streaks (AS) using AO: "crack," "band," and "hypopigmented." The first 2 were very similar and they differed in size; the third type showed specific clinical features. Comet lesions appeared as hyper-reflective round lesions on AO imaging. In all eyes, the cone mosaic appeared reduced inside the streaks compared to the neighboring areas (13,532.8 ± 1,366.5 cones/mm² vs 16,817.1 ± 1,263.0 cones/mm² respectively).

CONCLUSION

Using AO imaging in PXE-related retinopathy, we were able to observe the presence of the photoreceptors within the angioid streaks, differentiate 3 types of angioid streaks, based on size and reflective features, and identify the very small crystalline bodies not identifiable using other retinal imaging techniques.

The Relation between Body Mass Index and Retinal Photoreceptor Morphology and Microvascular Changes Measured with Adaptive Optics (rtx1) High-Resolution Imaging

Background

Overweight and obese patients are at risk for diabetes, cardiovascular disorders, and microvascular complications. The rtx1^TM (Imagine Eyes, France) is a microscope that allows near histological visualizations of cones and retinal microcirculation.

Objective

This study analysed the cones and retinal microvascular changes in a group of 47 healthy women with different BMI values. Participants were divided into 2 groups: the BMI group (28 women with BMI >/25) and the control group (19 lean women with BMI <25).

Results

The lumen and diameter of retinal arteries were not significantly different between groups. There were significant differences in the thickness of arteriole walls. The WLR and WCSA values differed significantly between the control and BMI groups (for WLR 0.25 ± 0.03 vs. 0.29 ± 0.03, p < 0.001; for WCSA 4136.7 ± 1140.0 vs. 5217.3 ± 944.0, respectively, p < 0.001). In healthy eyes, cone density and morphology were not affected by weight.

Conclusions

Retinal image analysis with rtx1 offers a novel noninvasive measurement of early changes in retinal vasculature that are not detectable during routine clinical examination. Abnormalities of retinal arterioles found by rtx1™examination should be considered as a strong risk factor for cardiovascular changes resulting from overweight and obesity.

Human Eye Optics within a Non-Euclidian Geometrical Approach and Some Implications in Vision Prosthetics Design

An analogy with our previously published theory on the ionospheric auroral gyroscope provides a new perspective in human eye optics. Based on cone cells' real distribution, we model the human eye macula as a pseudospherical surface. This allows the rigorous description of the photoreceptor cell densities in the parafoveal zones modeled further by an optimized paving method. The hexagonal photoreceptors' distribution has been optimally projected on the elliptical pseudosphere, thus designing a prosthetic array counting almost 7000 pixel points. Thanks to the high morphological similarities to a normal human retina, the visual prosthesis performance in camera-free systems might be significantly improved.

Solar retinopathy-correlation between adaptive optics and spectral domain optical coherence tomography with visual acuity

BACKGROUND

To study the characteristics of photoreceptors on adaptive optics (AO) in patients of solar retinopathy and its correlation to changes in spectral domain optical coherence tomography (SDOCT) and visual acuity.

METHODS AND MATERIAL

This is a cross-sectional observational study of six eyes of five patients with clinically diagnosed solar retinopathy. Five age-matched controls were included for comparison. A flood-illuminated adaptive optics retinal camera (AO; rtx1, Imagine Eyes, Orsay, France) was used to image the photoreceptors and a spectral domain optical coherence tomography (SDOCT; Spectralis™ Heidelberg Engineering, Germany) was used to study the retinal layers in these patients. The corrected distance visual acuity (CDVA) was assessed using Snellen's chart.

RESULTS

Defects on the SDOCT were smaller (0.25 to 0.75°) at the fovea compared with AO (more than 1°). The cone mosaic was preserved beyond 1°. The cone count from the foveal center at 0.75, 1, 2, and 3° was decreased in all patients of solar retinopathy (mean value 5352) compared with age-matched controls (mean value 15693). A corresponding increase in spacing (mean value 19.13) compared with controls (mean value 9.34) was also observed. The CDVA ranged from 20/30 to 20/80. There was no statistically significant relationship between cone density, at any of the eccentricities measured, with CDVA or OCT defect (p > 0.05, for all).

CONCLUSIONS

Adaptive optics is a sensitive and accurate tool to analyze photoreceptor damage in solar maculopathy. It can be used as an adjunct for better understanding of the pathology and to observe or predict changes in these patients.

Photoreceptor assessment in focal laser-treated central serous chorioretinopathy using adaptive optics and fundus autofluorescence

This study analyzed cone density, cone mosaic, and fundus autofluorescence (FAF) images in patients with focal laser-treated central serous chorioretinopathy (CSC).Observational case series.Forty-two eyes of 21 patients with unilateral treated CSC and bilateral best-corrected visual acuity of 1.0 (decimal fraction) were included. FAF and cone mosaic images were obtained in all patients with an adaptive optics fundus camera. Densities were recorded at 20 points throughout the macula, and choroidal thicknesses were measured.Mean choroidal thicknesses were 419.95 ± 110.33 μm in normal eyes, 459.09 ± 90.07 μm in eyes with active CSC, and 438.61 ± 107.57 μm in treated eyes. The highest density of cones in healthy eyes was 38146 cones/mm, with a 5.66-μm intercellular space (IS), at 700 μm temporal to the center. In eyes with treated CSC, the highest density was 32749 cones/mm, with a 6.13-μm IS, at 500 μm nasal to the center. In all quadrants, median values of maximum cone density were significantly higher in healthy eyes (P = .02, P = .003, P = .0001, and P = .001). Three types of lesions were identified on FAF and were correlated with those on cone mosaic images. Strong correlations were detected between the presence of hypoautofluorescent lesions on the first FAF image and a greater difference between maximum values of photoreceptor density (r = 0.46, P = .03), as well as between the presence of hypoautofluorescent lesions and the duration of pathology (r = 0.68, P < .001).The presence of hypoautofluorescent lesions and the duration of pathology were negative prognostic factors in CSC. Laser treatment could prevent photoreceptor loss.

Quality improvement of adaptive optics retinal images using conditional adversarial networks

The adaptive optics (AO) technique is widely used to compensate for ocular aberrations and improve imaging resolution. However, when affected by intraocular scatter, speckle noise, and other factors, the quality of the retinal image will be degraded. To effectively improve the image quality without increasing the imaging system's complexity, the post-processing method of image deblurring is adopted. In this study, we proposed a conditional adversarial network-based method for directly learning an end-to-end mapping between blurry and restored AO retinal images. The proposed model was validated on synthetically generated AO retinal images and real retinal images. The restoration results of synthetic images were evaluated with the metrics of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), perceptual distance, and error rate of cone counting. Moreover, the blind image quality index (BIQI) was used as the no-reference image quality assessment (NR-IQA) algorithm to evaluate the restoration results on real AO retinal images. The experimental results indicate that the images restored by the proposed method have sharper quality and higher signal-to-noise ratio (SNR) when compared with other state-of-the-art methods, which has great practical significance for clinical research and analysis.

CHANGES IN VISUAL ACUITY AND PHOTORECEPTOR DENSITY USING ADAPTIVE OPTICS AFTER RETINAL DETACHMENT REPAIR

PURPOSE

To quantify changes in photoreceptor density using adaptive optics fundus camera in patients after retinal detachment (RD) and to correlate them with macular involvement and best-corrected visual acuity.

METHODS

At 1 and 3 months (M1 and M3) after vitrectomy, 194 patients underwent adaptive optics imagery in both eyes, at 5 locations, that we matched between time points using anatomical landmarks. Twenty-two patients (10 fovea-OFF [OFF] and 12 fovea-ON [ON]) had matched and analyzable adaptive optics images. We used analysis of variance for repeated measures.

RESULTS

Best-corrected visual acuity (logarithm of the minimum angle of resolution and Snellen equivalent [SE]) was significantly different between OFF and ON RDs at baseline: 2.0 (2.3-0.95) (SE: 20/2000) versus 0 (0.1-0) (SE: 20/20); at M1: 0.35 (0.5-0.1) (SE: 20/40) versus 0.05 (0-0.1) (SE: 20/25); and at M3: 0.25 (0.3-0.1) (SE: 20/32) versus 0 (0-0) (SE: 20/20). We observed that cone density was stable in fellow eyes between M1 and M3 (P = 0.67); decreased in treated eyes than in fellow eyes (P < 0.05); and increased postoperatively in the ON group (P = 0.02) but not in the OFF group (P = 0.97). Visual acuity and RD type were independently correlated with cone density (P = 0.004, P = 0.000).

CONCLUSION

Postoperative cone density was reduced in OFF RD, but also in the ON group, although the drop recovered during the 3-month follow-up. Cone density was significantly correlated with both visual acuity and type of RD at both time points.

Cellular imaging of inherited retinal diseases using adaptive optics

Adaptive optics (AO) is an insightful tool that has been increasingly applied to existing imaging systems for viewing the retina at a cellular level. By correcting for individual optical aberrations, AO offers an improvement in transverse resolution from 10-15 μm to ~2 μm, enabling assessment of individual retinal cell types. One of the settings in which its utility has been recognised is that of the inherited retinal diseases (IRDs), the genetic and clinical heterogeneity of which warrants better cellular characterisation. In this review, we provide a summary of the basic principles of AO, its integration into multiple retinal imaging modalities and its clinical applications, focusing primarily on IRDs. Furthermore, we present a comprehensive summary of AO-based cellular findings in IRDs according to their associated disease-causing genes.

Repeatability of Adaptive Optics Automated Cone Measurements in Subjects With Retinitis Pigmentosa and Novel Metrics for Assessment of Image Quality

Purpose

We determine the intersession repeatability of cone measurements via flood-illuminated adaptive optics (AO) imaging in patients with retinitis pigmentosa (RP), to better differentiate variation due to imaging inaccuracies versus pathology-driven change.

Methods

A total of 25 4° × 4° AO images were acquired three times on the same day in 10 subjects with RP, registered in i2K Retina, and cones were identified using a custom-built MATLAB algorithm. Nine equally spaced regions of interest were selected for each imaging set. A subset of subjectively “poor” and “good” quality images was selected by three independent graders, analyzed using cone density, cone location similarity (CLS) and cone spacing, and compared to age-matched normals.

Results

The coefficient of variation (CoV), repeatability, and percent repeatability of automated cone density were slightly higher in patients with RP compared to age-matched normals, but showed no statistically significant difference. The standard deviation of CLS and cone spacing of nearest-neighbor distance demonstrated a statistically significant difference between good- and poor-quality images.

Conclusions

Repeatability of automated cone density measurements in patients with RP is comparable to normals. Misidentification of cones due to image quality variability is a major limitation of automated cone counting algorithms in patients with RP. Our study suggests that CLS and cone spacing metrics could be used to help define image quality and, thus, increase confidence in automated cone counts in patients with RP.

Translational Relevance

The novel AO image quality assessment metrics described in our study could help to improve patient image interpretation, prognosis, and longitudinal care.

Distribution of mid-peripheral cones in emmetropic and myopic subjects using adaptive optics flood illumination camera

PURPOSE

We measured in vivo cone photoreceptors up to 24° of eccentricity along the horizontal meridian of healthy human retina. We also investigated the impact on cone densities of axial eye length elongation occurring with myopia.

METHODS

Using a flood illumination device coupled with an adaptive optics system, rtx1™, ( www.imagine-eyes.com), 55 right healthy retinas were imaged along the horizontal (i.e. nasal and temporal) meridian over a 48° field (i.e. from 3° to 24° each 3°). Then, cones were manually detected within 80 × 80 pixel regions of interest. Cone density and packing geometry (i.e. number of neighbours) were calculated (AOdetect software™). Subjects were divided into three groups: a group of 36 emmetropic (i.e. refractive error from -0.25D to +0.50D) subjects; a group of 10 low myopic subjects (i.e. refractive error from -0.50D to -2.50D); and a group of nine high myopic subjects (i.e. >-2.50D).

RESULTS

Cone density decreased with eccentricity in both semi-meridians. The decrease in cone photoreceptors occurred mainly in the first 9°. The difference of cone density between the nasal and temporal semi-meridian increased with eccentricity from 0.6% at 3° to 26% at 24°. Average cone density of emmetropes (850 cones deg^-2 or 11 087 cones mm^-2 ), low myopes (830 cones deg^-2 or 9731 cones mm^-2 ), and high myopes (912 cones deg^-2 or 9744 cones mm^-2 ), suggested that the retinas of the high myopic subjects were more stretched than the low myopic subjects retinas and even more stretched than that of the emmetropes. The axial eyeball elongation (square of the ratio of the axial eye length of 9%) seems to explain the cone density (11%) difference between emmetropes and low myopes. However, while the eyeball elongation between low and high myopes is still important (i.e. 11%), cone density difference between both populations was negligible (i.e. 3%). The ratio of cone density varied from -17% to 22% as a function of eccentricity involving that the retinal stretching is not uniform along the horizontal meridian.

CONCLUSION

The difference of cone density (i.e. cone mm^-2 ) between groups supports the hypothesis that the retina is stretched with the eyeball elongation. However, this elongation does not seem to be uniform along the horizontal meridian favouring the hypothesis of a local elongation of the retina.

Adaptive Optics (rtx1) High-Resolution Imaging of Photoreceptors and Retinal Arteries in Patients with Diabetic Retinopathy

BACKGROUND

Diabetic retinopathy (DR) is the leading cause of impaired vision in patients with diabetes mellitus. An adaptive optics retinal camera (rtx1™; Imagine Eyes, France) was used to capture images of cones and retinal arteries from patients with DR.

OBJECTIVE

Cone parameters (density, interphotoreceptor distance, and regularity) and retinal artery parameters (wall thickness, lumen diameter, WLR, and WCSA) were analyzed in 36 patients with nonproliferative DR (NPDR; 22 with mild NPDR and 14 with moderate NPDR) and in 20 healthy volunteers (the control group).

RESULTS

Cone density at 2° eccentricities was significantly lower in the DR compared to the control group (19822 ± 4342 cells/mm² vs. 24722 ± 3507 cells/mm², respectively). Cone density and regularity decreased with increasing severity of DR. The artery walls were significantly thicker in the DR group. The WLR and WCSA differed significantly between the DR and the control groups (WLR 0.339 ± 0.06 vs. 0.254 ± 0.04; WCSA 5567 ± 1140 vs. 4178 ± 944, respectively).

CONCLUSIONS

Decreased cone regularity and density are seen in patients with mild and moderate NPDR. Abnormalities of retinal arterioles show signs of arteriolar dysfunction in DR. Retinal image analysis with the rtx1 offers a novel noninvasive measurement of early changes in the neural cells and retina vasculature in diabetic eyes.

Automated identification of cone photoreceptors in adaptive optics optical coherence tomography images using transfer learning

Automated measurements of the human cone mosaic requires the identification of individual cone photoreceptors. The current gold standard, manual labeling, is a tedious process and can not be done in a clinically useful timeframe. As such, we present an automated algorithm for identifying cone photoreceptors in adaptive optics optical coherence tomography (AO-OCT) images. Our approach fine-tunes a pre-trained convolutional neural network originally trained on AO scanning laser ophthalmoscope (AO-SLO) images, to work on previously unseen data from a different imaging modality. On average, the automated method correctly identified 94% of manually labeled cones when compared to manual raters, from twenty different AO-OCT images acquired from five normal subjects. Voronoi analysis confirmed the general hexagonal-packing structure of the cone mosaic as well as the general cone density variability across portions of the retina. The consistency of our measurements demonstrates the high reliability and practical utility of having an automated solution to this problem.

High-resolution imaging of photoreceptors in healthy human eyes using an adaptive optics retinal camera

PURPOSE

To determine the effects of age on perifoveal cone density in healthy subjects using adaptive optics.

METHODS

Healthy subjects of various ages were imaged using an adaptive optics retinal camera (RTX-1^® Imagine Eyes, Orsay, France). All patients underwent a comprehensive ophthalmologic examination and retinal imaging using spectral-domain optical coherence tomography (Spectralis^®, Heidelberg Engineering, Heidelberg, Germany). Cone density together with cone spacing and cone mosaic packing were measured in the nasal and temporal area 450 µm from the fovea. A multivariate analysis was performed to determine which of the following parameters were related to a decrease in cone density: age, axial length, central macular thickness, and retrofoveal choroidal thickness.

RESULTS

One hundred and sixty-seven eyes of 101 subjects aged 6-78 years were studied. Perifoveal cone density significantly decreased with age (R² = 0.17, p<0.01). Inversely, cone spacing increased with age (R²=0.18, p<0.01). There was no change in the cone packing mosaic (p>0.05). The mean coefficient of variation between fellow eyes was 3.9%. Age and axial length were related to a cone density decrease, while choroidal and retinal thicknesses did not affect cone metrics in healthy subjects.

CONCLUSIONS

A moderate perifoveal cone loss occurs with age. The precise consequences of these findings on visual function should be investigated. In addition to a better understanding of normal retinal anatomy, these results could act as a comparative database for further studies on normal and diseased retinas.

High speed adaptive optics ophthalmoscopy with an anamorphic point spread function

Retinal imaging working with a line scan mechanism and a line camera has the potential to image the eye with a near-confocal performance at the high frame rate, but this regime has difficulty to collect sufficient imaging light while adequately digitize the optical resolution in adaptive optics imaging. To meet this challenge, we have developed an adaptive optics line scan ophthalmoscope with an anamorphic point spread function. The instrument uses a high-speed line camera to acquire the retinal image and act as a confocal gate. Meanwhile, it employs a digital micro-mirror device to modulate the imaging light into a line of point sources illuminating the retina. The anamorphic mechanism ensures adequate digitization of the optical resolution and increases light collecting efficiency. We demonstrate imaging of the living human retina with cellular level resolution at a frame rate of 200 frames/second (FPS) with a digitization of 512 × 512 pixels over a field of view of 1.2° × 1.2°. We have assessed cone photoreceptor structure in images acquired at 100, 200, and 800 FPS in 2 normal human subjects, and confirmed that retinal images acquired at high speed rendered macular cone mosaic with improved measurement repeatability.

Use of focus measure operators for characterization of flood illumination adaptive optics ophthalmoscopy image quality

Adaptive optics flood illumination ophthalmoscopy (AO-FIO) allows imaging of the cone photoreceptor in the living human retina. However, clinical interpretation of the AO-FIO image remains challenging due to suboptimal quality arising from residual uncorrected wavefront aberrations and rapid eye motion. An objective method of assessing image quality is necessary to determine whether an AO-FIO image is suitable for grading and diagnostic purpose. In this work, we explore the use of focus measure operators as a surrogate measure of AO-FIO image quality. A set of operators are tested on data sets acquired at different focal depths and different retinal locations from healthy volunteers. Our results demonstrate differences in focus measure operator performance in quantifying AO-FIO image quality. Further, we discuss the potential application of the selected focus operators in (i) selection of the best quality AO-FIO image from a series of images collected at the same retinal location and (ii) assessment of longitudinal changes in the diseased retina. Focus function could be incorporated into real-time AO-FIO image processing and provide an initial automated quality assessment during image acquisition or reading center grading.

Visual resolution and cone spacing in the nasal and inferior retina

PURPOSE

To determine the retinal eccentricity at which cones are no longer an observable substitute for ganglion cells on nasal and inferior parafoveal visual acuity.

METHOD

Visual acuities were measured on 12 healthy volunteers, under dynamic adaptive optic aberrations correction (crx1™) in white light, from 0° to 6°, every two degrees, along the nasal and inferior retinal meridians. Cone spacing was measured on images of the retina acquired using an adaptive optic flood illumination retina camera (rtx1™) at the same eccentricity, except at 0°.

RESULTS

Cone spacing increased by around 0.13 min of arc per degree of eccentricity and a difference of 7% between both meridians was observed (higher cone spacing in the inferior retinal meridian). Visual resolution was higher in the nasal retinal meridian (difference of around 28% or 0.15 logMAR at 6°). Cone spacing can predict minimum angle of resolution (MAR) at 2° in both semi retinal meridians. In the inferior retinal meridian, MAR measurements are fairly well predicted by Watson's 50% mathematical model based on the midget retinal ganglion cell density. Along the nasal retinal meridian, the measured MAR lies between Watson's 50% and 100% models.

CONCLUSIONS

At 2° of eccentricity, cone density accurately predicts visual resolution in both the nasal and inferior retina, supporting the idea that only 50% of the foveal midget retinal ganglion cells determine VA. The 50% model can also predict VA in the inferior retinal meridian at 4° and 6° of eccentricity. However, the 50% model underestimated visual acuity in the nasal retinal meridian at 4° and 6° of eccentricity consistent with the partially overlapping ON and OFF midget retinal ganglion cell receptive fields.

Distribution of cone density, spacing and arrangement in adult healthy retinas with adaptive optics flood illumination

The aim of this article is to analyse cone density, spacing and arrangement using an adaptive optics flood illumination retina camera (rtx1^™) on a healthy population. Cone density, cone spacing and packing arrangements were measured on the right retinas of 109 subjects at 2°, 3°, 4°, 5° and 6° of eccentricity along 4 meridians. The effects of eccentricity, meridian, axial length, spherical equivalent, gender and age were evaluated. Cone density decreased on average from 28 884 ± 3 692 cones/mm², at 2° of eccentricity, to 15 843 ± 1 598 cones/mm² at 6°. A strong inter-individual variation, especially at 2°, was observed. No important difference of cone density was observed between the nasal and temporal meridians or between the superior and inferior meridians. However, the horizontal and vertical meridians differed by around 14% (T-test, p<0.0001). Cone density, expressed in units of area, decreased as a function of axial length (r² = 0.60), but remained constant (r² = 0.05) when cone density is expressed in terms of visual angle supporting the hypothesis that the retina is stretched during the elongation of the eyeball. Gender did not modify the cone distribution. Cone density was slightly modified by age but only at 2°. The older group showed a smaller density (7%). Cone spacing increased from 6,49 ± 0,42 μm to 8,72 ± 0,45 μm respectively between 2° and 6° of eccentricity. The mosaic of the retina is mainly triangularly arranged (i.e. cells with 5 to 7 neighbors) from 2° to 6°. Around half of the cells had 6 neighbors.

Retinal Photoreceptors and Microvascular Changes in Prediabetes Measured with Adaptive Optics (rtx1™): A Case-Control Study

BACKGROUND

Patients with prediabetes are at risk for diabetes, cardiovascular events, and microvascular complications. The rtx1 (Imagine Eyes, France) permits early detection of changes in the retinal photoreceptors and vessels.

OBJECTIVE

Cone parameters and retinal microvasculature were analyzed with the rtx1 in 12 prediabetic patients and 22 healthy subjects. The analysis was based on cone density (DM), interphotoreceptor distance (SM), cone packing regularity, and retinal vessel parameters: wall thickness, lumen diameter (LD), wall-to-lumen ratio (WLR), and cross-sectional area of the vascular wall.

RESULTS

DM in the prediabetic group was not significantly lower than that in the control group (18,935 ± 1713 cells/mm2 and 19,900 ± 2375 cells/mm2, respectively; p = 0.0928). The LD and WLR means differed significantly between the prediabetic and the control groups (LD 94.3 ± 10.9 versus 101.2 ± 15, p = 0.022; WLR 0.29 ± 0.05 versus 0.22 ± 0.03, p < 0.05). A multivariate regression analysis showed that the WLR was significantly correlated with BMI and total cholesterol.

CONCLUSIONS

Abnormalities found in rtx1 examinations indicated early signs of arteriolar dysfunction, prior to impaired glucose tolerance progressing to diabetes. The rtx1 retinal image analysis offers noninvasive measurement of early changes in the vasculature that routine clinical examination cannot detect.

Comparing Parafoveal Cone Photoreceptor Mosaic Metrics in Younger and Older Age Groups Using an Adaptive Optics Retinal Camera

BACKGROUND AND OBJECTIVE

To analyze cone mosaic metrics on adaptive optics (AO) images as a function of retinal eccentricity in two different age groups using a commercial flood illumination AO device.

PATIENTS AND METHODS

Fifty-three eyes of 28 healthy subjects divided into two age groups were imaged using an AO flood-illumination camera (rtx1; Imagine Eyes, Orsay, France). A 16° × 4° field was obtained horizontally. Cone-packing metrics were determined in five neighboring 50 µm × 50 µm regions. Both retinal (cones/mm² and µm) and visual (cones/degrees² and arcmin) units were computed.

RESULTS

Results for cone mosaic metrics at 2°, 2.5°, 3°, 4°, and 5° eccentricity were compatible with previous AO scanning laser ophthalmoscopy and histology data. No significant difference was observed between the two age groups.

CONCLUSIONS

The rtx1 camera enabled reproducible measurements of cone-packing metrics across the extrafoveal retina. These findings may contribute to the development of normative data and act as a reference for future research. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:45-50.].

Human photoreceptor cone density measured with adaptive optics technology (rtx1 device) in healthy eyes: Standardization of measurements

The anatomic structures of the anterior segment of the eye enable correct reception of stimuli by the retina, which contains receptors that receive light impulses and transmit them to the visual cortex. The aim of this study was to assess the effect of the size of the sampling window in an adaptive optics (AO) flood-illumination retinal camera (rtx1) on cone density measurements in the eyes of healthy individuals and to investigate the differences in cone density and spacing in different quadrants of the retina. Thirty-three subjects with no ophthalmic or systemic disease underwent a detailed ophthalmologic examination. Photographs of retinal fragments 3 degrees from the fovea were taken using the rtx1 AO retinal camera. We used sampling windows with 3 sizes (50 × 50, 100 × 100, and 250 × 250 μm). Cone density, spacing, and shape were determined using AOdetect software. The median (interquartile range) cone density was 19,269 (4964) cones/mm. There were statistically significant differences between measurements taken with the 50/50 and 250/250-m windows. There were no significant differences in the cone spacing results between any of the windows examined, but the measurements differed according to location between the superior and temporal quadrants. The most common cone shape was hexagonal (47.6%) for all window sizes and locations. These findings may help in the development of a normative database for variation in cone density in healthy subjects and to allow the best window to be chosen for obtain the most correct values for eccentricity measurements of 3 degrees. In our study, the optimal sampling window was 100 × 100 μm.

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging

PURPOSE

To present en face optical coherence tomography (OCT) images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities.

METHODS

En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory) and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering)) were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO) and microperimetry.

RESULTS

Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE) pathology due to segmentation error at the level of Bruch's membrane (BM). Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities.

CONCLUSIONS

Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis.

Relationship between Psychophysical Measures of Retinal Ganglion Cell Density and In Vivo Measures of Cone Density in Glaucoma

PURPOSE

Considerable between-individual variation in retinal ganglion cell (RGC) density exists in healthy individuals, making identification of change from normal to glaucoma difficult. In ascertaining local cone-to-RGC density ratios in healthy individuals, we wished to investigate the usefulness of objective cone density estimates as a surrogate of baseline RGC density in glaucoma patients, and thus a more efficient way of identifying early changes.

DESIGN

Exploratory cohort study.

PARTICIPANTS

Twenty glaucoma patients (60% women) with a median age of 54 years and mean deviation (MD) in the visual field of -5 dB and 20 healthy controls (70% women) with a median age of 57 years and a mean MD of 0 dB were included.

METHODS

Glaucoma patients and healthy participants underwent in vivo cone imaging at 4 locations of 8.8° eccentricity with a modified Heidelberg Retina Angiograph HRA2 (scan angle, 3°). Cones were counted using an automated program. Retinal ganglion cell density was estimated at the same test locations from peripheral grating resolution acuity thresholds.

MAIN OUTCOME MEASURES

Retinal cone density, estimated RGC density, and cone-to-RGC ratios in glaucoma patients and healthy controls.

RESULTS

Median cone-to-RGC density was 3.51:1 (interquartile range [IQR], 2.59:1-6.81:1) in glaucoma patients compared with 2.35:1 (IQR, 1.83:1-2.82:1) in healthy participants. Retinal ganglion cell density was 33% lower in glaucoma patients than in healthy participants; however, cone density was very similar in glaucoma patients (7248 cells/mm²) and healthy controls (7242 cells/mm²). The area under the receiver operator characteristic curve was 0.79 (95% confidence interval [CI], 0.71-0.86) for both RGC density and cone-to-RGC ratio and 0.49 (95% CI, 0.39-0.58) for cone density.

CONCLUSIONS

Local measurements of cone density do not differ significantly from normal in glaucoma patients despite large differences in RGC density. There was no statistically significant association between RGC density and cone density in the normal participants, and the range of cone-to-RGC density ratios was relatively large in healthy controls. These findings suggest that estimates of baseline RGC density from cone density are unlikely to be precise and offer little advantage over determination of RGC alone in the identification of early glaucomatous change.

Selective and complementary use of Optical Coherence Tomography and Fluorescein Angiography in retinal practice

The current field of posterior pole and retinal imaging of the human eye has expanded into detailed analyses of the macula, retinal periphery, individual retinal layers, vitreoretinal interface, imaging of the choroid and the optic nerve head. The challenge in retinal imaging is the enduring pursuit of deeper penetration into tissues, increased resolution to the cellular level, and interpretation of observations. How much deeper can we go and with what resolution and reproducibility? These are fundamental questions for experts in search of novel imaging modalities. New discoveries may resolve existing controversies, but inevitably stimulate new questions. Emerging technologies in retinal imaging include adaptive optics retinal imaging and optical coherence tomography-based retinal angiography.

In this review, the focus of our discussion will be the discrepancy between the findings (interpretation) of one imaging technology that do not agree or are not even found with a complementary technology. If a clearly seen abnormality is present with one technology but absent in another, what are the possible explanations? Following is a summary of key concepts of retinal and optic nerve imaging modalities and current controversies regarding their interpretation and/or limitations.

MULTIMODAL IMAGING OF POSTERIOR POLAR ANNULAR CHOROIDAL DYSTROPHY

BACKGROUND

Posterior polar annular choroidal dystrophy (PPACD) is a rare disease. Patients with PPACD show loss of retinal pigment epithelium and choriocapillaries surrounding the vascular arcades and optic nerve.

METHODS

Two patients with PPACD were evaluated with multimodal imaging, including fundus autofluorescence (FAF) and adaptive optics (AO).

REPORT OF CASES

One patient (32 year old, one eye) with PPACD was followed up for 3 years. Best-corrected visual acuity (BCVA) was stable at 20/40, whereas a slight enlargement of paravascular atrophy of pigment epithelium was observed at fundus autofluorescence (FAF). Adaptive optics obtained at last examination showed reduced density of foveal cone photoreceptors. The second patient (30 year old, two eyes) with PPACD showed bilateral normal BCVA, associated with reduction in the density of foveal cone photoreceptors.

CONCLUSION

At FAF, longitudinal follow-up of PPACD showed progression of the paravascular atrophy of the pigment epithelium. Foveal cone photoreceptors can be reduced even in the presence of preserved visual acuity.

Understanding the changes of cone reflectance in adaptive optics flood illumination retinal images over three years

Although there is increasing interest in the investigation of cone reflectance variability, little is understood about its characteristics over long time scales. Cone detection and its automation is now becoming a fundamental step in the assessment and monitoring of the health of the retina and in the understanding of the photoreceptor physiology. In this work we provide an insight into the cone reflectance variability over time scales ranging from minutes to three years on the same eye, and for large areas of the retina (≥ 2.0 × 2.0 degrees) at two different retinal eccentricities using a commercial adaptive optics (AO) flood illumination retinal camera. We observed that the difference in reflectance observed in the cones increases with the time separation between the data acquisitions and this may have a negative impact on algorithms attempting to track cones over time. In addition, we determined that displacements of the light source within 0.35 mm of the pupil center, which is the farthest location from the pupil center used by operators of the AO camera to acquire high-quality images of the cone mosaic in clinical studies, does not significantly affect the cone detection and density estimation.

Hessian-LoG filtering for enhancement and detection of photoreceptor cells in adaptive optics retinal images

Automated analysis of retinal images plays a vital role in the examination, diagnosis, and prognosis of healthy and pathological retinas. Retinal disorders and the associated visual loss can be interpreted via quantitative correlations, based on measurements of photoreceptor loss. Therefore, it is important to develop reliable tools for identification of photoreceptor cells. In this paper, an automated algorithm is proposed, based on the use of the Hessian-Laplacian of Gaussian filter, which allows enhancement and detection of photoreceptor cells. The performance of the proposed technique is evaluated on both synthetic and high-resolution retinal images, in terms of packing density. The results on the synthetic data were compared against ground truth as well as cone counts obtained by the Li and Roorda algorithm. For the synthetic datasets, our method showed an average detection accuracy of 98.8%, compared to 93.9% for the Li and Roorda approach. The packing density estimates calculated on the retinal datasets were validated against manual counts and the results obtained by a proprietary software from Imagine Eyes and the Li and Roorda algorithm. Among the tested methods, the proposed approach showed the closest agreement with manual counting.

Semi-automated identification of cones in the human retina using circle Hough transform

A large number of human retinal diseases are characterized by a progressive loss of cones, the photoreceptors critical for visual acuity and color perception. Adaptive Optics (AO) imaging presents a potential method to study these cells in vivo. However, AO imaging in ophthalmology is a relatively new phenomenon and quantitative analysis of these images remains difficult and tedious using manual methods. This paper illustrates a novel semi-automated quantitative technique enabling registration of AO images to macular landmarks, cone counting and its radius quantification at specified distances from the foveal center. The new cone counting approach employs the circle Hough transform (cHT) and is compared to automated counting methods, as well as arbitrated manual cone identification. We explore the impact of varying the circle detection parameter on the validity of cHT cone counting and discuss the potential role of using this algorithm in detecting both cones and rods separately.

Variability in Human Cone Topography Assessed by Adaptive Optics Scanning Laser Ophthalmoscopy

PURPOSE

To assess between- and within-individual variability of macular cone topography in the eyes of young adults.

DESIGN

Observational case series.

METHODS

Cone photoreceptors in 40 eyes of 20 subjects aged 19-29 years with normal maculae were imaged using a research adaptive optics scanning laser ophthalmoscope. Refractive errors ranged from -3.0 diopters (D) to 0.63 D and differed by <0.50 D in fellow eyes. Cone density was assessed on a 2-dimensional sampling grid over the central 2.4 mm × 2.4 mm. Between-individual variability was evaluated by coefficient of variation (COV). Within-individual variability was quantified by maximum difference and root mean square (RMS). Cones were cumulated over increasing eccentricity.

RESULTS

Peak densities of foveal cones are 168 162 ± 23 529 cones/mm(2) (mean ± SD) (COV = 0.14). The number of cones within the cone-dominated foveola (0.8-0.9 mm diameter) is 38 311 ± 2319 (COV = 0.06). The RMS cone density difference between fellow eyes is 6.78%, and the maximum difference is 23.6%. Mixed-model statistical analysis found no difference in the association between eccentricity and cone density in the superior/nasal (P = .8503), superior/temporal (P = .1551), inferior/nasal (P = .8609), and inferior/temporal (P = .6662) quadrants of fellow eyes.

CONCLUSIONS

New instrumentation imaged the smallest foveal cones, thus allowing accurate assignment of foveal centers and assessment of variability in macular cone density in a large sample of eyes. Though cone densities vary significantly in the fovea, the total numbers of foveolar cones are very similar both between and within subjects. Thus, the total number of foveolar cones may be an important measure of cone degeneration and loss.

Meaning of visualizing retinal cone mosaic on adaptive optics images

PURPOSE

To explore the anatomic correlation of the retinal cone mosaic on adaptive optics images.

DESIGN

Retrospective nonconsecutive observational case series.

METHODS

A retrospective review of the multimodal imaging charts of 6 patients with focal alteration of the cone mosaic on adaptive optics was performed. Retinal diseases included acute posterior multifocal placoid pigment epitheliopathy (n = 1), hydroxychloroquine retinopathy (n = 1), and macular telangiectasia type 2 (n = 4). High-resolution retinal images were obtained using a flood-illumination adaptive optics camera. Images were recorded using standard imaging modalities: color and red-free fundus camera photography; infrared reflectance scanning laser ophthalmoscopy, fluorescein angiography, indocyanine green angiography, and spectral-domain optical coherence tomography (OCT) images.

RESULTS

On OCT, in the marginal zone of the lesions, a disappearance of the interdigitation zone was observed, while the ellipsoid zone was preserved. Image recording demonstrated that such attenuation of the interdigitation zone co-localized with the disappearance of the cone mosaic on adaptive optics images. In 1 case, the restoration of the interdigitation zone paralleled that of the cone mosaic after a 2-month follow-up.

CONCLUSION

Our results suggest that the interdigitation zone could contribute substantially to the reflectance of the cone photoreceptor mosaic. The absence of cones on adaptive optics images does not necessarily mean photoreceptor cell death.