The reliability of parafoveal cone density measurements

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.

Intervisit Reproducibility of Foveal Cone Density Metrics

Purpose

To assess longitudinal reproducibility of metrics of foveal density (peak cone density [PCD], cone density centroid [CDC], and 80th percentile centroid area) in participants with normal vision.

Methods

Participants (n = 19; five male and 14 female) were imaged at two time points (average interval of 3.2 years) using an adaptive optics scanning light ophthalmoscope (AOSLO). Foveally centered regions of interest (ROIs) were extracted from AOSLO montages. Cone coordinate matrices were semiautomatically derived for each ROI, and cone mosaic metrics were calculated.

Results

On average, there were no significant changes in cone mosaic metrics between visits. The average ± SD PCD was 187,000 ± 20,000 cones/mm2 and 189,000 ± 21,700 cones/mm2 for visits 1 and 2, respectively (P = 0.52). The average ± SD density at the CDC was 183,000 ± 19,000 cones/mm2 and 184,000 ± 20,800 cones/mm2 for visits 1 and 2, respectively (P = 0.78). The average ± SD 80th percentile isodensity contour area was 15,400 ± 1800 µm2 and 15,600 ± 1910 µm2 for visits 1 and 2, respectively (P = 0.57).

Conclusions

Foveal cone mosaic density metrics were highly reproducible in the cohort examined here, although further study is required in more diverse populations.

Translational Relevance

Determination of the normative longitudinal changes in foveal cone topography is key for evaluating longitudinal measures of foveal cone topography in patients with progressive retinal dystrophies.

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.

Intergrader agreement of foveal cone topography measured using adaptive optics scanning light ophthalmoscopy

The foveal cone mosaic can be directly visualized using adaptive optics scanning light ophthalmoscopy (AOSLO). Previous studies in individuals with normal vision report wide variability in the topography of the foveal cone mosaic, especially the value of peak cone density (PCD). While these studies often involve a human grader, there have been no studies examining intergrader reproducibility of foveal cone mosaic metrics. Here we re-analyzed published AOSLO foveal cone images from 44 individuals to assess the relationship between the cone density centroid (CDC) location and the location of PCD. Across 5 graders with variable experience, we found a measurement error of 11.7% in PCD estimates and higher intergrader reproducibility of CDC location compared to PCD location (p < 0.0001). These estimates of measurement error can be used in future studies of the foveal cone mosaic, and our results support use of the CDC location as a more reproducible anchor for cross-modality analyses.

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.

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.

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.

Fully Automated Estimation of Spacing and Density for Retinal Mosaics

Purpose

To introduce and validate a novel, fully automated algorithm for determining pointwise intercell distance (ICD) and cone density.

Methods

We obtained images of the photoreceptor mosaic from 14 eyes of nine subjects without retinal pathology at two time points using an adaptive optics scanning laser ophthalmoscope. To automatically determine ICD, the radial average of the discrete Fourier transform (DFT) of the image was analyzed using a multiscale, fit-based algorithm to find the modal spacing. We then converted the modal spacing to ICD by assuming a hexagonally packed mosaic. The reproducibility of the algorithm was assessed between the two datasets, and accuracy was evaluated by comparing the results against those calculated from manually identified cones. Finally, the algorithm was extended to determine pointwise ICD and density in montages by calculating modal spacing over an overlapping grid of regions of interest (ROIs).

Results

The differences of DFT-derived ICD between the test and validation datasets were 3.2% ± 3.5% (mean ± SD), consistent with the differences in directly calculated ICD (1.9% ± 2.9%). The average ICD derived by the automated method was not significantly different between the development and validation datasets and was equivalent to the directly calculated ICD. When applied to a full montage, the automated algorithm produced estimates of cone density across retinal eccentricity that well match prior empiric measurements.

Conclusions

We created an accurate, repeatable, and fully automated algorithm for determining ICD and density in both individual ROIs and across entire montages.

Translational Relevance

The use of fully automated and validated algorithms will enable rapid analysis over the full photoreceptor montage.

Interocular symmetry, intraobserver repeatability, and interobserver reliability of cone density measurements in the 13-lined ground squirrel

BACKGROUND

The 13-lined ground squirrel (13-LGS) possesses a cone-dominant retina that is highly amenable to non-invasive high-resolution retinal imaging. The ability for longitudinal assessment of a cone-dominant photoreceptor mosaic with an adaptive optics scanning light ophthalmoscope (AOSLO) has positioned the 13-LGS to become an accessible model for vision research. Here, we examine the interocular symmetry, repeatability, and reliability of cone density measurements in the 13-LGS.

METHODS

Thirteen 13-LGS (18 eyes) were imaged along the vertical meridian with a custom AOSLO. Regions of interest were selected superior and inferior to the optic nerve head, including the cone-rich visual streak. Non-confocal split-detection was used to capture images of the cone mosaic. Five masked observers each manually identified photoreceptors for 26 images three times and corrected an algorithm's cell identification outputs for all 214 images three times. Intraobserver repeatability and interobserver reliability of cone density were characterized using data collected from all five observers, while interocular symmetry was assessed in five animals using the average values of all observers. The distribution of image quality for all images in this study was assessed with open-sourced software.

RESULTS

Manual identification was less repeatable than semi-automated correction for four of the five observers. Excellent repeatability was seen from all observers (ICC = 0.997-0.999), and there was good agreement between repeat cell identification corrections in all five observers (range: 9.43-25.71 cells/degree2). Reliability of cell identification was significantly different in two of the five observers, and worst in images taken from hibernating 13-LGS. Interocular symmetry of cone density was seen in the five 13-LGS assessed. Image quality was variable between blur- and pixel intensity-based metrics.

CONCLUSIONS

Interocular symmetry with repeatable cone density measurements suggest that the 13-LGS is well-suited for longitudinal examination of the cone mosaic using split-detection AOSLO. Differences in reliability highlight the importance of observer training and automation of AOSLO cell detection. Cone density measurements from hibernating 13-LGS are not repeatable. Additional studies are warranted to assess other metrics of cone health to detect deviations from normal 13-LGS in future models of cone disorder in this species.

"For Mass Eye and Ear Special Issue" Adaptive Optics in the Evaluation of Diabetic Retinopathy

Retinal imaging is a fundamental tool for clinical and research efforts in the evaluation and management of diabetic retinopathy. Adaptive optics (AO) is an imaging technique that enables correction of over 90% of the optical aberrations of an individual eye induced primarily by the tear film, cornea and lens. The two major tasks of any AO system are to measure the optical imperfections of the eye and to then compensate for these aberrations to generate a corrected wavefront of reflected light from the eye. AO scanning laser ophthalmoscopy (AOSLO) provides a theoretical lateral resolution limit of 1.4 μm, allowing the study of microscopic features of the retinal vascular and neural tissue. AOSLO studies have revealed irregularities of the photoreceptor mosaic, vascular loss, and details of vascular lesions in diabetic eyes that may provide new insight into development, regression, and response to therapy of diabetic eye disease.

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.

The Reliability of Cone Density Measurements in the Presence of Rods

Purpose

Recent advances in adaptive optics scanning light ophthalmoscopy (AOSLO) have enabled visualization of cone inner segments through nonconfocal split-detection, in addition to rod and cone outer segments revealed by confocal reflectance. Here, we examined the interobserver reliability of cone density measurements in both AOSLO imaging modalities.

Methods

Five normal subjects (nine eyes) were imaged along the horizontal and vertical meridians using a custom AOSLO with confocal and nonconfocal split-detection modalities. The resulting images were montaged using a previously described semiautomatic algorithm. Regions of interest (ROIs) were selected from the confocal montage at 190 μm, and from split-detection and confocal montages at 900 and 1800 μm from the fovea. Four observers (three experts, one naïve) manually identified cone locations in each ROI, and these locations were used to calculate bound densities. Intraclass correlation coefficients and Dice's coefficients were calculated to assess interobserver agreement.

Results

Interobserver agreement was high in cone-only images (confocal 190 μm: 0.85; split-detection 900 μm: 0.91; split-detection 1800 μm: 0.89), moderate in confocal images at 900 μm (0.68), and poor in confocal images at 1800 μm (0.24). Excluding the naïve observer data substantially increased agreement within confocal images (190 μm: 0.99; 900 μm: 0.80; 1800 μm: 0.68).

Conclusions

Interobserver measurements of cone density are more reliable in rod-free retinal images. Moreover, when using manual cell identification, it is essential that observers are trained, particularly for confocal AOSLO images.

Translational Relevance

This study underscores the need for additional reliability studies in eyes containing pathology where identifying cones can be substantially more difficult.

Intraobserver Repeatability and Interobserver Reproducibility of Ellipsoid Zone Measurements in Retinitis Pigmentosa

Purpose

To examine repeatability and reproducibility of ellipsoid zone (EZ) width measurements in patients with retinitis pigmentosa (RP) using a longitudinal reflectivity profile (LRP) analysis.

Methods

We examined Bioptigen optical coherence tomography (OCT) scans from 48 subjects with RP or Usher syndrome. Nominal scan lengths were 6, 7, or 10 mm, and the lateral scale of each scan was calculated using axial length measurements. LRPs were generated from OCT line scans, and the peak corresponding to EZ was manually identified using ImageJ. The locations at which the EZ peak disappeared were used to calculate EZ width. Each scan was analyzed twice by each of two observers, who were masked to their previous measurements and those of the other observer.

Results

On average, horizontal width (HW) was significantly greater than vertical width (VW), and there was high interocular symmetry for both HW and VW. We observed excellent intraobserver repeatability with intraclass correlation coefficients (ICCs) ranging from 0.996 to 0.998 for HW and VW measurements. Interobserver reproducibility was also excellent for both HW (ICC = 0.989; 95% confidence interval [CI] = 0.983–0.995) and VW (ICC = 0.991; 95% CI = 0.985–0.996), with no significant bias observed between observers.

Conclusions

EZ width can be measured using LRPs with excellent repeatability and reproducibility. Our observation of greater HW than VW is consistent with previous observations in RP, though the reason for this anisotropy remains unclear.

Translational Relevance

We describe repeatability and reproducibility of a method for measuring EZ width in patients with RP or Usher syndrome. This approach could facilitate measurement of retinal band thickness and/or intensity.

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.

Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning

We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excellent view into retinal structure and health, provides new perspectives into well known pathologies, and allows clinicians to monitor the effectiveness of experimental treatments. The MultiDimensional Recurrent Neural Network (MDRNN) approach developed in this paper is the first method capable of reliably and automatically identifying cones in both healthy retinas and retinas afflicted with Stargardt disease. Therefore, it represents a leap forward in the computational image processing of AOSLO images, and can provide clinical support in on-going longitudinal studies of disease progression and therapy. We validate our method using images from healthy subjects and subjects with the inherited retinal pathology Stargardt disease, which significantly alters image quality and cone density. We conduct a thorough comparison of our method with current state-of-the-art methods, and demonstrate that the proposed approach is both more accurate and appreciably faster in localizing cones. As further validation to the method’s robustness, we demonstrate it can be successfully applied to images of retinas with pathologies not present in the training data: achromatopsia, and retinitis pigmentosa.

Repeatability and Reproducibility of In Vivo Cone Density Measurements in the Adult Zebrafish Retina

Zebrafish (Danio rerio) are widely used as an experimental model for a wide range of retinal diseases. Previously, optical coherence tomography (OCT) was introduced for quantitative analysis of the zebrafish cone photoreceptor cell mosaic; however no data exists on the intersession reproducibility or intrasession repeatability of such measurements. We imaged 14 wild-type (WT) fish three times each, with 48 h between each time point. En face images of the UV cone mosaic were generated from the OCT volume scans at each time point. These images were then aligned and the overlapping area cropped for analysis. Using a semiautomated cone-counting algorithm, a single observer identified each cone to calculate the cone density for every image, counting each image twice (84 total counts). The OCT cone density measurements were found to have an intersession reproducibility of 0.9988 (95% CI = 0.9978-0.9999) and an intrasession repeatability of 136.0 ± 10.5 cones/mm² (about 0.7%). Factors affecting image quality include gill movement during acquisition of the OCT volume and variable inclusion of non-UV cone mosaics in the contours used to generate the en face images.

REPEATABILITY AND LONGITUDINAL ASSESSMENT OF FOVEAL CONE STRUCTURE IN CNGB3-ASSOCIATED ACHROMATOPSIA

PURPOSE

Congenital achromatopsia is an autosomal recessive disease causing substantial reduction or complete absence of cone function. Although believed to be a relatively stationary disorder, questions remain regarding the stability of cone structure over time. In this study, the authors sought to assess the repeatability of and examine longitudinal changes in measurements of central cone structure in patients with achromatopsia.

METHODS

Forty-one subjects with CNGB3-associated achromatopsia were imaged over a period of between 6 and 26 months using optical coherence tomography and adaptive optics scanning light ophthalmoscopy. Outer nuclear layer (ONL) thickness, ellipsoid zone (EZ) disruption, and peak foveal cone density were assessed.

RESULTS

ONL thickness increased slightly compared with baseline (0.184 μm/month, P = 0.02). The EZ grade remained unchanged for 34/41 subjects. Peak foveal cone density did not significantly change over time (mean change 1% per 6 months, P = 0.126).

CONCLUSION

Foveal cone structure showed little or no change in this group of subjects with CNGB3-associated achromatopsia. Over the time scales investigated (6-26 months), achromatopsia seems to be a structurally stable condition, although longer-term follow-up is needed. These data will be useful in assessing foveal cone structure after therapeutic intervention.

Reliability and Repeatability of Cone Density Measurements in Patients With Stargardt Disease and RPGR-Associated Retinopathy

Purpose

To assess reliability and repeatability of cone density measurements by using confocal and (nonconfocal) split-detector adaptive optics scanning light ophthalmoscopy (AOSLO) imaging. It will be determined whether cone density values are significantly different between modalities in Stargardt disease (STGD) and retinitis pigmentosa GTPase regulator (RPGR)–associated retinopathy.

Methods

Twelve patients with STGD (aged 9–52 years) and eight with RPGR-associated retinopathy (aged 11–31 years) were imaged using both confocal and split-detector AOSLO simultaneously. Four graders manually identified cone locations in each image that were used to calculate local densities. Each imaging modality was evaluated independently. The data set consisted of 1584 assessments of 99 STGD images (each image in two modalities and four graders who graded each image twice) and 928 RPGR assessments of 58 images (each image in two modalities and four graders who graded each image twice).

Results

For STGD assessments the reliability for confocal and split-detector AOSLO was 67.9% and 95.9%, respectively, and the repeatability was 71.2% and 97.3%, respectively. The differences in the measured cone density values between modalities were statistically significant for one grader. For RPGR assessments the reliability for confocal and split-detector AOSLO was 22.1% and 88.5%, respectively, and repeatability was 63.2% and 94.5%, respectively. The differences in cone density between modalities were statistically significant for all graders.

Conclusions

Split-detector AOSLO greatly improved the reliability and repeatability of cone density measurements in both disorders and will be valuable for natural history studies and clinical trials using AOSLO. However, it appears that these indices may be disease dependent, implying the need for similar investigations in other conditions.

Relationships Between Spatial Contrast Sensitivity and Parafoveal Cone Density in Normal Subjects and Patients With Retinal Degeneration

BACKGROUND AND OBJECTIVE

To investigate the relationship between spatial contrast sensitivity (CS) and parafoveal cone density (PCD).

PATIENTS AND METHODS

Fifteen healthy individuals (mean age: 26.1 years ± 4.5 years) and nine patients with hereditary retinal degeneration (mean age: 31.6 years ± 13.4 years) without media opacities were studied. The CS was measured by CSV-1000 (VectorVision, Greenville, OH). The cone mosaic was photographed with an adaptive optics scanning laser ophthalmoscope (AOSLO) with a 1° × 1° field of view centered on the fovea. The PCD was calculated in an annular area with radii of 0.38° and 0.43°. The CS was converted to the logarithm (logCS), and the area under the logCS function (AULCSF) was determined.

RESULTS

The AULCSF was significantly and positively correlated with the PCD in the control (R² = 0.522; P = .003) and retinal degeneration (R² = 0.514; P = .03) groups.

CONCLUSION

PCD can predict the spatial contrast sensitivity in normal subjects or patients with retinal degeneration without media opacities. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:106-113.].

Photoreceptor-Based Biomarkers in AOSLO Retinal Imaging

Improved understanding of the mechanisms underlying inherited retinal degenerations has created the possibility of developing much needed treatments for these relentless, blinding diseases. However, standard clinical indicators of retinal health (such as visual acuity and visual field sensitivity) are insensitive measures of photoreceptor survival. In many retinal degenerations, significant photoreceptor loss must occur before measurable differences in visual function are observed. Thus, there is a recognized need for more sensitive outcome measures to assess therapeutic efficacy as numerous clinical trials are getting underway. Adaptive optics (AO) retinal imaging techniques correct for the monochromatic aberrations of the eye and can be used to provide nearly diffraction-limited images of the retina. Many groups routinely are using AO imaging tools to obtain in vivo images of the rod and cone photoreceptor mosaic, and it now is possible to monitor photoreceptor structure over time with single cell resolution. Highlighting recent work using AO scanning light ophthalmoscopy (AOSLO) across a range of patient populations, we review the development of photoreceptor-based metrics (e.g., density/geometry, reflectivity, and size) as candidate biomarkers. Going forward, there is a need for further development of automated tools and normative databases, with the latter facilitating the comparison of data sets across research groups and devices. Ongoing and future clinical trials for inherited retinal diseases will benefit from the improved resolution and sensitivity that multimodal AO retinal imaging affords to evaluate safety and efficacy of emerging therapies.

Automated measurements of human cone photoreceptor density in healthy and degenerative retina by region-based segmentation

Purpose

The purpose of this study was to develop an algorithm based on region-based segmentation for automated calculations of human cone photoreceptor density of en face images obtained by an adaptive optics scanning laser ophthalmoscope (AOSLO).

Subjects and methods

Cone mosaics of 15 eyes of 15 healthy subjects were photographed by a custom-built AOSLO. The cone density was calculated at 0.5, 1.0, and 1.5 mm temporal from the fovea using a region-based segmentation method (RSM) developed in our laboratory. The cone density was also determined by a manual identification method (MIM) and a conventional spatial filtering method (SFM). The cone densities of three eyes of three patients with retinal degeneration were calculated by the three methods and compared to the results from normal eyes.

Results

The cone densities in healthy retinas determined by the RSM at 0.5, 1.0, and 1.5 mm temporal from the fovea were 28,436, 21,233, and 13,620 cells/mm², respectively. These densities were in good agreement with a histological study and with in vivo AOSLO studies. The cone densities determined by RSM were different from those determined by MIM with a difference of 5% in healthy eyes. In eyes with retinal degeneration, with the appropriate threshold-level settings or spatial frequency bandwidth, the cone density measured by MIM was significantly closer to that measured by RSM than by SFM.

Conclusion

These results suggest that our method is more stable than conventional methods in cases of non-periodical photoreceptor structures such as the affected retinal area. Our method can be used in the longitudinal follow-up of retinal degenerative diseases and to determine the effect of therapy.

Visualization of Photoreceptors in Birdshot Chorioretinopathy Using Adaptive Optics Scanning Laser Ophthalmoscopy: A Pilot Study

PURPOSE

Adaptive optics scanning laser ophthalmoscopy (AOSLO) allows en face visualization of specific layers of the retina. This pilot study evaluated the ability of AOSLO to visualize photoreceptor integrity in patients with birdshot chorioretinopathy (BCR).

METHOD

A total of 16 consecutive patients with HLA-A29+ BCR were imaged using the prototype Apaeros retinal imaging system. Images of high quality were aligned with infrared reflectance photos and correlated with spectral domain optical coherence tomography (SD-OCT).

RESULTS

Images of four eyes of three patients were of sufficient quality to allow posterior pole montage and point-to-point correlation with SD-OCT. Areas of photoreceptor disruption on SD-OCT were seen as patchy areas of loss on AOSLO, whereas areas of intact interdigitation zone and inner segment/outer segment junction correlated with normal appearing photoreceptors on AOSLO.

CONCLUSIONS

Using AOSLO, we found one instance of subclinical photoreceptor disruption not seen on SD-OCT. Ultimately, there are unique challenges associated with imaging BCR patients using AOSLO.

Distribution differences of macular cones measured by AOSLO: Variation in slope from fovea to periphery more pronounced than differences in total cones

Large individual differences in cone densities occur even in healthy, young adults with low refractive error. We investigated whether cone density follows a simple model that some individuals have more cones, or whether individuals differ in both number and distribution of cones. We quantified cones in the eyes of 36 healthy young adults with low refractive error using a custom adaptive optics scanning laser ophthalmoscope. The average cone density in the temporal meridian was, for the mean±SD, 43,216±6039, 27,466±3496, 14,996±1563, and 12,207±1278cones/mm² for 270, 630, 1480, and 2070μm from the foveal center. Cone densities at 630μm retinal eccentricity were uncorrelated to those at 2070μm, ruling out models with a constant or proportional relation of cone density to eccentricity. Subjects with high central macula cone densities had low peripheral cone densities. The cone density ratio (2070:630μm) was negatively correlated with cone density at 630μm, consistent with variations in the proportion of peripheral cones migrating towards the center. We modelled the total cones within a central radius of 7deg, using the temporal data and our published cone densities for temporal, nasal, superior, and inferior meridians. We computed an average of 221,000 cones. The coefficient of variation was 0.0767 for total cones, but higher for samples near the fovea. Individual differences occur both in total cones and other developmental factors related to cone distribution.

Adaptive optics scanning laser ophthalmoscope imaging: technology update

Adaptive optics (AO) retinal imaging has become very popular in the past few years, especially within the ophthalmic research community. Several different retinal techniques, such as fundus imaging cameras or optical coherence tomography systems, have been coupled with AO in order to produce impressive images showing individual cell mosaics over different layers of the in vivo human retina. The combination of AO with scanning laser ophthalmoscopy has been extensively used to generate impressive images of the human retina with unprecedented resolution, showing individual photoreceptor cells, retinal pigment epithelium cells, as well as microscopic capillary vessels, or the nerve fiber layer. Over the past few years, the technique has evolved to develop several different applications not only in the clinic but also in different animal models, thanks to technological developments in the field. These developments have specific applications to different fields of investigation, which are not limited to the study of retinal diseases but also to the understanding of the retinal function and vision science. This review is an attempt to summarize these developments in an understandable and brief manner in order to guide the reader into the possibilities that AO scanning laser ophthalmoscopy offers, as well as its limitations, which should be taken into account when planning on using it.

Mathematical and computational models of the retina in health, development and disease

The retina confers upon us the gift of vision, enabling us to perceive the world in a manner unparalleled by any other tissue. Experimental and clinical studies have provided great insight into the physiology and biochemistry of the retina; however, there are questions which cannot be answered using these methods alone. Mathematical and computational techniques can provide complementary insight into this inherently complex and nonlinear system. They allow us to characterise and predict the behaviour of the retina, as well as to test hypotheses which are experimentally intractable. In this review, we survey some of the key theoretical models of the retina in the healthy, developmental and diseased states. The main insights derived from each of these modelling studies are highlighted, as are model predictions which have yet to be tested, and data which need to be gathered to inform future modelling work. Possible directions for future research are also discussed. Whilst the present modelling studies have achieved great success in unravelling the workings of the retina, they have yet to achieve their full potential. For this to happen, greater involvement with the modelling community is required, and stronger collaborations forged between experimentalists, clinicians and theoreticians. It is hoped that, in addition to bringing the fruits of current modelling studies to the attention of the ophthalmological community, this review will encourage many such future collaborations.

Effects of Intraframe Distortion on Measures of Cone Mosaic Geometry from Adaptive Optics Scanning Light Ophthalmoscopy

Purpose

To characterize the effects of intraframe distortion due to involuntary eye motion on measures of cone mosaic geometry derived from adaptive optics scanning light ophthalmoscope (AOSLO) images.

Methods

We acquired AOSLO image sequences from 20 subjects at 1.0, 2.0, and 5.0° temporal from fixation. An expert grader manually selected 10 minimally distorted reference frames from each 150-frame sequence for subsequent registration. Cone mosaic geometry was measured in all registered images (n = 600) using multiple metrics, and the repeatability of these metrics was used to assess the impact of the distortions from each reference frame. In nine additional subjects, we compared AOSLO-derived measurements to those from adaptive optics (AO)-fundus images, which do not contain system-imposed intraframe distortions.

Results

We observed substantial variation across subjects in the repeatability of density (1.2%–8.7%), inter-cell distance (0.8%–4.6%), percentage of six-sided Voronoi cells (0.8%–10.6%), and Voronoi cell area regularity (VCAR) (1.2%–13.2%). The average of all metrics extracted from AOSLO images (with the exception of VCAR) was not significantly different than those derived from AO-fundus images, though there was variability between individual images.

Conclusions

Our data demonstrate that the intraframe distortion found in AOSLO images can affect the accuracy and repeatability of cone mosaic metrics. It may be possible to use multiple images from the same retinal area to approximate a “distortionless” image, though more work is needed to evaluate the feasibility of this approach.

Translational Relevance

Even in subjects with good fixation, images from AOSLOs contain intraframe distortions due to eye motion during scanning. The existence of these artifacts emphasizes the need for caution when interpreting results derived from scanning instruments.

Reliability and Repeatability of Cone Density Measurements in Patients with Congenital Achromatopsia

Adaptive optics scanning light ophthalmoscopy (AOSLO) allows non-invasive assessment of the cone photoreceptor mosaic. Confocal AOSLO imaging of patients with achromatopsia (ACHM) reveals an altered reflectivity of the remaining cone structure, making identification of the cells more challenging than in normal retinas. Recently, a "split-detector" AOSLO imaging method was shown to enable direct visualization of cone inner segments in patients with ACHM. Several studies have demonstrated gene replacement therapy effective in restoring cone function in animal models of ACHM and human trials have on the horizon, making the ability to reliably assess cone structure increasingly important. Here we sought to examine whether absolute estimates of cone density obtained from split-detector and confocal AOSLO images differed from one another and whether the inter- and intra-observer reliability is significantly different between these modes. These findings provide an important foundation for evaluating the role of these images as tools to assess the efficacy of future gene therapy trials.

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.

Spontaneous Regeneration of Human Photoreceptor Outer Segments

Photoreceptors are damaged in many common eye diseases, such as macular degeneration, retinal detachment, and retinitis pigmentosa. The development of methods to promote the repair or replacement of affected photoreceptors is a major goal of vision research. In this context, it would be useful to know whether photoreceptors are capable of undergoing some degree of spontaneous regeneration after injury. We report a subject who lost retinal function in a wide zone around the optic disc, giving rise to massive enlargement of the physiological blind spot. Imaging with an adaptive optics scanning laser ophthalmoscope (AOSLO) showed depletion of cone outer segments in the affected retina. A year later visual function had improved, with shrinkage of the enlarged blind spot. AOSLO imaging showed repopulation of cone outer segments, although their density remained below normal. There was a one-to-one match between sites of formerly missing outer segments and new outer segments that had appeared over the course of the year's recovery. This correspondence provided direct morphological evidence that damaged cones are capable, under some circumstances, of generating new outer segments.