Deep learning-enabled volumetric cone photoreceptor segmentation in adaptive optics optical coherence tomography images of normal and diseased eyes.

Objective quantification of photoreceptor cell morphology, such as cell diameter and outer segment length, is crucial for early, accurate, and sensitive diagnosis and prognosis of retinal neurodegenerative diseases. Adaptive optics optical coherence tomography (AO-OCT) provides three-dimensional (3-D) visualization of photoreceptor cells in the living human eye. The current gold standard for extracting cell morphology from AO-OCT images involves the tedious process of 2-D manual marking. To automate this process and extend to 3-D analysis of the volumetric data, we propose a comprehensive deep learning framework to segment individual cone cells in AO-OCT scans. Our automated method achieved human-level performance in assessing cone photoreceptors of healthy and diseased participants captured with three different AO-OCT systems representing two different types of point scanning OCT: spectral domain and swept source.

Cone photoreceptor dysfunction in retinitis pigmentosa revealed by optoretinography.

Retinitis pigmentosa (RP) is the most common group of inherited retinal degenerative diseases, whose most debilitating phase is cone photoreceptor death. Perimetric and electroretinographic methods are the gold standards for diagnosing and monitoring RP and assessing cone function. However, these methods lack the spatial resolution and sensitivity to assess disease progression at the level of individual photoreceptor cells, where the disease originates and whose degradation causes vision loss. High-resolution retinal imaging methods permit visualization of human cone cells in vivo but have only recently achieved sufficient sensitivity to observe their function as manifested in the cone optoretinogram. By imaging with phase-sensitive adaptive optics optical coherence tomography, we identify a biomarker in the cone optoretinogram that characterizes individual cone dysfunction by stimulating cone cells with flashes of light and measuring nanometer-scale changes in their outer segments. We find that cone optoretinographic responses decrease with increasing RP severity and that even in areas where cone density appears normal, cones can respond differently than those in controls. Unexpectedly, in the most severely diseased patches examined, we find isolated cones that respond normally. Short-wavelength-sensitive cones are found to be more vulnerable to RP than medium- and long-wavelength-sensitive cones. We find that decreases in cone response and cone outer-segment length arise earlier in RP than changes in cone density but that decreases in response and length are not necessarily correlated within single cones.

Revealing How Color Vision Phenotype and Genotype Manifest in Individual Cone Cells.

Purpose: Psychophysical and genetic testing provide substantial information about color vision phenotype and genotype. However, neither reveals how color vision phenotypes and genotypes manifest themselves in individual cones, where color vision and its anomalies are thought to originate. Here, we use adaptive-optics phase-sensitive optical coherence tomography (AO-PSOCT) to investigate these relationships. Methods: We used AO-PSOCT to measure cone function-optical response to light stimulation-in each of 16 human subjects with different phenotypes and genotypes of color vision (five color-normal, three deuteranopic, two protanopic, and six deuteranomalous trichromatic subjects). We classified three spectral types of cones (S, M, and L), and we measured cone structure-namely cone density, cone mosaic arrangement, and spatial arrangement of cone types. Results: For the different phenotypes, our cone function results show that (1) color normals possess S, M, and L cones; (2) deuteranopes are missing M cones but are normal otherwise; (3) protanopes are missing L cones but are normal otherwise; and (4) deuteranomalous trichromats are missing M cones but contain evidence of at least two subtypes of L cones. Cone function was consistent with the subjects' genotype in which only the first two M and L genes in the gene array are expressed and was correlated with the estimated spectral separation between photopigments, including in the deuteranomalous trichromats. The L/M cone ratio was highly variable in the color normals. No association was found between cone density and the genotypes and phenotypes investigated, and the cone mosaic arrangement was altered in the dichromats. Conclusions: AO-PSOCT is a novel method for assessing color vision phenotype and genotype in single cone cells.

Cone photoreceptor classification in the living human eye from photostimulation-induced phase dynamics.

Human color vision is achieved by mixing neural signals from cone photoreceptors sensitive to different wavelengths of light. The spatial arrangement and proportion of these spectral types in the retina set fundamental limits on color perception, and abnormal or missing types are responsible for color vision loss. Imaging provides the most direct and quantitative means to study these photoreceptor properties at the cellular scale in the living human retina, but remains challenging. Current methods rely on retinal densitometry to distinguish cone types, a prohibitively slow process. Here, we show that photostimulation-induced optical phase changes occur in cone cells and carry substantial information about spectral type, enabling cones to be differentiated with unprecedented accuracy and efficiency. Moreover, these phase dynamics arise from physiological activity occurring on dramatically different timescales (from milliseconds to seconds) inside the cone outer segment, thus exposing the phototransduction cascade and subsequent downstream effects. We captured these dynamics in cones of subjects with normal color vision and a deuteranope, and at different macular locations by: (i) marrying adaptive optics to phase-sensitive optical coherence tomography to avoid optical blurring of the eye, (ii) acquiring images at high speed that samples phase dynamics at up to 3 KHz, and (iii) localizing phase changes to the cone outer segment, where photoactivation occurs. Our method should have broad appeal for color vision applications in which the underlying neural processing of photoreceptors is sought and for investigations of retinal diseases that affect cone function.