The high resolution of adaptive optics optical coherence tomography (AO-OCT) allows 3-dimensional imaging of individual cone photoreceptors in vivo. Histology has revealed that short-wavelength-sensitive (S) cones have distinct structural features compared with medium-wavelength-sensitive (M) and long-wavelength-sensitive (L) cones. Quantifying these structural features in images of living human retinas may provide a simpler and quicker method for identifying S cones than by imaging cone function (e.g., optoretinography). Here, we present a quantitative method for using AO-OCT measurements of cone structure in a support vector machine (SVM) classifier to identify individual S cones. For every cone cell, we measured six key structural parameters: inner segment length (ISL), outer segment length (OSL), inner segment / outer segment conjunction (IS/OS) diameter, cone outer-segment tip (COST) diameter, IS/OS reflectance, and COST reflectance. ISL and OSL were determined from depth differences between reflections of the external limiting membrane (ELM) and IS/OS, and IS/OS and COST, respectively. Each reflection’s depth was measured with sub-pixel accuracy using Gaussian interpolation; its diameter was measured using the gradient information from the en face projection at that depth. Among 6,398 analyzed cones in six subjects, we found S cones had significantly longer ISLs, shorter OSLs, and wider IS/OS diameters than did cones of other types. We used these structural differences in our SVM model to classify cone spectral types and compared results with cone optoretinography. In five of the six subjects, S cones were identified with F1 scores ranging from 0.78 to 0.93.
Numerous retinal pathologies affect cone photoreceptor photopigment density, making it a potentially attractive functional biomarker for detecting and tracking disease progression. Conventional methods to measure photopigment density include psychophysical color matching, microspectrophotometry, and retinal densitometry, but these are either subjective, measure the aggregate response / change of thousands of cones, or are performed ex vivo. Recently, we have developed a method to measure spectral sensitivities of individual human cone photoreceptors objectively, non-invasively, and in vivo with adaptive optics optical coherence tomography (AO-OCT). In preliminary results we have observed variability in the spectral sensitivities of individual cones of the same type (S, M or L) that we hypothesize attributes to inter-cone variations in photopigment density. If correct this may be of significant clinical interest. Here, we test this hypothesis by (1) deriving an expression for the relative photopigment densities of individual cone photoreceptors based on a theoretical model of the cone absorption process and (2) using this expression to estimate photopigment density from our AO-OCT measurements of spectral sensitivity. Our mean spectral sensitivity measurements align well to Stockman & Sharpe's wellrecognized cone fundamentals with a total least-squared error of 0.12 and confidence intervals (CI) <0.36, <0.025 and <0.017 for S, M, and L cones, respectively. The substantive variability in individual cone spectral sensitivities once related to photopigment density exhibits a distribution of standard deviation = 0.177 for a group of 703 cones. This indicates a two-fold difference in light sensitivity between the least sensitive cone (least amount of photopigment) and the most sensitive cone (largest amount of photopigment) for 95% of the cones measured. Furthermore, we found relative photopigment density decreased with increasing retinal eccentricity from nasal to temporal retina at 3.8° eccentricity with a slope of -0.19/° (p < .001). Both density distribution and eccentricity dependence are consistent with the literature.
Adaptive optics (AO) measures and corrects ocular wavefront aberrations, enabling cellular-resolution retinal imaging and stimulation, and enhanced visual performance. AO is a dynamic control system that must track and correct temporal changes in ocular aberrations in real time. This necessitates a wavefront sensor whose integration time and readout time are sufficiently short to minimize the latency of the feedback system and hence maximize AO performance. Most current ophthalmic AO systems use long wavefront sensor integration times on the order of 10−60 ms, resulting in long latencies, low AO loop rates (typically no greater than 10 Hz with a discontinuous-exposure scheme), and small AO closed-loop bandwidths (less than 1.5 Hz). Here, by using an integration time (0.126 ms) that is 100−500× shorter and a readout speed of the wavefront sensor that is 3−100× higher, we reduce the AO latency and increase the AO bandwidth by ~30× to 37.5 Hz. Although our wavefront sensor detects 100−500× fewer photons, our noise analysis shows that this limited number of photons is still sufficient for diffraction-limited wavefront measurements and hence our wavefront sensing is photon-efficient. We demonstrate that the resulting ultrafast AO running at 233 Hz significantly improves aberration correction and retinal image quality over conventional AO in a clinically-relevant scenario.
The quantitative evaluation of peripheral ocular optics is essential in both myopia research and the investigation of visual performance in people with normal and compromised central vision. We have developed a widefield scanning wavefront sensor (WSWS) capable of multidirectional scanning while maintaining natural central fixation at the primary gaze. This Shack-Hartmann-based WSWS scans along any retinal meridian by using a unique scanning method that involves the concurrent operation of a motorized rotary stage (horizontal scan) and a goniometer (vertical scan). To showcase the capability of the WSWS, we tested scanning along four meridians including a 60° horizontal, 36° vertical, and two 36° diagonal scans, each completed within a time frame of 5 seconds.
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