Persistent Dark Cones in Oligocone Trichromacy Revealed by Multimodal Adaptive Optics Ophthalmoscopy

Extracting spacing-derived estimates of rod density in healthy retinae

Quantification of the rod photoreceptor mosaic using adaptive optics scanning light ophthalmoscopy (AOSLO) remains challenging. Here we demonstrate a method for deriving estimates of rod density and rod:cone ratio based on measures of rod spacing, cone numerosity, and cone inner segment area. Twenty-two AOSLO images with complete rod visualization were used to validate this spacing-derived method for estimating density. The method was then used to estimate rod metrics in an additional 105 images without complete rod visualization. The spacing-derived rod mosaic metrics were comparable to published data from histology. This method could be leveraged to develop large normative databases of rod mosaic metrics, though limitations persist with intergrader variability in assessing cone area and numerosity.

Twenty-five years of clinical applications using adaptive optics ophthalmoscopy [Invited]

Twenty-five years ago, adaptive optics (AO) was combined with fundus photography, thereby initiating a new era in the field of ophthalmic imaging. Since that time, clinical applications of AO ophthalmoscopy to investigate visual system structure and function in both health and disease abound. To date, AO ophthalmoscopy has enabled visualization of most cell types in the retina, offered insight into retinal and systemic disease pathogenesis, and been integrated into clinical trials. This article reviews clinical applications of AO ophthalmoscopy and addresses remaining challenges for AO ophthalmoscopy to become fully integrated into standard ophthalmic care.

Characterizing cone spectral classification by optoretinography

Light propagation in photoreceptor outer segments is affected by photopigment absorption and the phototransduction amplification cascade. Photopigment absorption has been studied using retinal densitometry, while recently, optoretinography (ORG) has provided an avenue to probe changes in outer segment optical path length due to phototransduction. With adaptive optics (AO), both densitometry and ORG have been used for cone spectral classification based on the differential bleaching signatures of the three cone types. Here, we characterize cone classification by ORG, implemented in an AO line-scan optical coherence tomography (OCT), and compare it against densitometry. The cone mosaics of five color normal subjects were classified using ORG showing high probability (∼0.99), low error (<0.22%), high test-retest reliability (∼97%), and short imaging durations (< 1 hour). Of these, the cone spectral assignments in two subjects were compared against AO-scanning laser opthalmoscope densitometry. High agreement (mean: 91%) was observed between the two modalities in these two subjects, with measurements conducted 6-7 years apart. Overall, ORG benefits from higher sensitivity and dynamic range to probe cone photopigments compared to densitometry, and thus provides greater fidelity for cone spectral classification.

Assessment of photoreceptor function with ultrafast retinal densitometry

The optical density of visual pigment can be measured by imaging the dark-adapted eye while bleaching with visible light. This measurement can be made for individual photoreceptor cells using adaptive optics; however, activation of the phototransduction cascade imparts rapid changes in phase that modulate the signal via optical interference. This limits utility because data must be averaged over many experimental runs. Here we used a "flood" illuminated adaptive optics system at 4000 fps, bright light to achieve rapid bleaching, and broad illumination bandwidth to mitigate interference effects. Data were super-resolved using the natural motion of the eye to overcome the reduced pixel resolution of the ultrafast camera. This approach was applied to classify the trichromatic cone photoreceptor mosaic at a single fixation locus within the foveal region of 3 healthy subjects. Subjects were dark adapted for 6 minutes to replenish cone photopigment. This was followed either directly by imaging at 555 ± 50 nm, or by first pre-adapting the retina to 700 nm light to preferentially deplete "L" cone pigment. A total of 3,252 cones were classified as either "S", "M", or "L" type based on clustering of the intensity data observed under these two conditions. Mean classification probability ranged from 99.3 to 99.8%, with individual cell probabilities exceeding 95% in 97.0 to 99.2% of cones. Accuracy of cone classification peaked when using the first 10-30 ms of data, with significant reductions in accuracy noted with the inclusion of data from later times. Our results show that rapid bleaching and data acquisition significantly improve the robustness of cell-resolved densitometry.

Cone Photoreceptors in Diabetic Patients

Purpose

Cones in diabetic patients are at risk due to metabolic and vascular changes. By imaging retinal vessel modeling at high magnification, we reduced its impact on cone distribution measurements. The retinal vessel images and retinal thickness measurements provided information about cone microenvironment.

Methods

We compared cone data in 10 diabetic subjects (28–78 yr) to our published norms from 36 younger and 10 older controls. All subjects were consented and tested in a manner approved by the Indiana University Institutional Review Board, which adhered to the Declaration of Helsinki. Custom adaptive optics scanning laser ophthalmoscopy (AOSLO) was used to image cones and retinal microcirculation. We counted cones in a montage of foveal and temporal retina, using four non-contiguous samples within 0.9–7 deg that were selected for best visibility of cones and least pathology. The data were fit with a two parameter exponential model: ln(cone density) = a ^* microns eccentricity + b. These results were compared to retinal thickness measurements from SDOCT.

Results

Diabetic cone maps were more variable than in controls and included patches, or unusually bright and dark cones, centrally and more peripherally. Model parameters and total cones within the central 14 deg of the macula differed across diabetic patients. Total cones fell into two groups: similar to normal for 5 vs. less than normal for 2 of 2 younger diabetic subjects and 3 older subjects, low but not outside the confidence limits. Diabetic subjects had all retinal vascular remodeling to varying degrees: microaneurysms; capillary thickening, thinning, or bends; and vessel elongation including capillary loops, tangles, and collaterals. Yet SD-OCT showed that no diabetic subject had a Total Retinal Thickness in any quadrant that fell outside the confidence limits for controls.

Conclusions

AOSLO images pinpointed widespread retinal vascular remodeling in all diabetic eyes, but the SDOCT showed no increased retinal thickness. Cone reflectivity changes were found in all diabetic patients, but significantly low cone density in only some. These results are consistent with early changes to neural, glial, or vascular components of the retinal without significant retinal thickening due to exudation.

Patches of Dysflective Cones in Eyes With No Known Disease

Purpose

To characterize the structure and function of patches of dysflective cones in the foveal region of subjects with normal vision and no known pathology. Dysflective cones are cones that have little or no reflective properties in optical coherence tomography (OCT) or adaptive optics scanning laser ophthalmoscope (AOSLO) images yet exhibit measurable function.

Methods

AOSLO images were surveyed for the presence of hyporeflective cone patches, and subjects were brought back for imaging to determine the changes in the hyporeflective region. Adaptive optics microperimetry (AOMP) was used to assess the function of hyporeflective patches in four subjects to determine that they did, in fact, contain dysflective cones. AOMP utilized a stimulus size of less than 1 arcmin to measure thresholds inside and outside the hyporeflective region.

Results

Nineteen out of 47 individuals retrospectively reviewed had one or more regions with hyporeflective cone patches in one or both eyes. Ten subjects with hyporeflective cone patches were brought back for imaging. Seven of the 10 had resolved at follow up, and in three subjects new hyporeflective patches appeared in a different location. All AOMP-measured subjects had measurable function in the dysflective cone region. Three out of four subjects showed no difference in light sensitivity in the dysflective region compared to adjacent areas, and one subject showed a 3× reduction in sensitivity in the area.

Conclusions

Patches of dysflective cone have been identified in subjects with normal vision and no known pathology, and we have observed instances where dysflective cones in these subjects regain normal reflective properties.