Significance: There are no label-free imaging descriptors related to physiological activity of inner retinal cells in the living human eye. A major reason is that inner retinal neurons are highly transparent and reflect little light, making them extremely difficult to visualize and quantify.
Aim: To measure physiologically-induced optical changes of inner retinal cells despite their challenging optical properties.
Approach: We developed an imaging method based on adaptive optics and optical coherence tomography (AO-OCT) and a suite of postprocessing algorithms, most notably a new temporal correlation method.
Results: We captured the temporal dynamics of entire inner retinal layers, of specific tissue types, and of individual cells across three different timescales from fast (seconds) to extremely slow (one year). Time correlation analysis revealed significant differences in time constant (up to 0.4 s) between the principal layers of the inner retina with the ganglion cell layer (GCL) being the most dynamic. At the cellular level, significant differences were found between individual GCL somas. The mean time constant of the GCL somas (0.69 ± 0.17 s) was ∼ 30 % smaller than that of nerve fiber bundles and inner plexiform layer synapses and processes. Across longer durations, temporal speckle contrast and time-lapse imaging revealed motion of macrophage-like cells (over minutes) and GCL neuron loss and remodeling (over one year).
Conclusions: Physiological activity of inner retinal cells is now measurable in the living human eye.
Retinitis Pigmentosa (RP), the most common group of inherited retinal degenerative diseases, is characterized by progressive loss of peripheral vision that surrounds an island of healthy central vision and a transition zone of reduced vision. The most debilitating phase of the disease is cone photoreceptor death whose biological mechanisms remain unknown. Traditional clinical methods such as perimetry and electroretinography are gold standards for diagnosing and monitoring RP and indirectly assessing cone function. Both methods, however, lack the spatial resolution and sensitivity to assess disease progression at the level of individual photoreceptor cells, where it begins. To address this need, we developed an imaging method based on phase-sensitive adaptive optics optical coherence tomography (PS-AO-OCT) that characterizes cone dysfunction in RP subjects by stimulating cone cells with flashes of light and measuring their resulting nanometer-scale changes in optical path length. We introduce new biomarkers to quantify cone dysfunction. We find cone function decreases with increasing RP severity and even in the healthy central area where cone structure appears normal, cones respond differently than cones in the healthy controls.
Human color vision is achieved by mixing neural signals from cone photoreceptors sensitive to long- (L), medium- (M), and short- (S) wavelength light. The spatial arrangement and proportion of these spectral types in the retina set fundamental limits on color perception, and abnormal or missing types lead to color vision deficiencies. In vivo mapping of the trichromatic cone mosaic provides the most direct and quantitative means to assess the role photoreceptors play in color vision, but current methods of in vivo imaging have important limitations that preclude their widespread use. In this study, we present a new method for classifying cones based on their unique phase response to flashes of quasi-monochromatic light. Our use of phase provides unprecedented efficiency (30 min of subject time/retinal location) and accuracy (<0.02% of uncertainty), thus making in vivo cone classification practical in a wide range of color vision applications. We used adaptive optics optical coherence tomography to resolve cone cells in 3D and customized post-processing algorithms to extract the phase signal of individual cones. We successfully characterized light-induced changes to the phase signature of cones under different illuminant spectra, established the relationship between this phase change and the three cone spectral types, and used this relationship to classify and map cones in two color normal subjects.
The ganglion cell (GC) is the primary cell type damaged by diseases of the optic nerve such as glaucoma. Assessment of individual glaucoma risk is limited by our inability to accurately measure GC degeneration and loss. Recently, adaptive optics optical coherence tomography (AO-OCT) has enabled visualization and quantification of individual GC layer (GCL) somas in normal, healthy subjects. Quantifying GC loss in glaucoma, however, requires longitudinal assessment of these cells, which is confounded by normal age-related loss of these same cells. The ability to distinguish between these two causes of cell death is therefore paramount for early detection of glaucoma. In this study, we assess the ability of our AO-OCT method to track individual GCL somas over a period of one year and of our post processing methods to reliably measure soma loss rates. In four normal subjects with no history of ocular disease, we measured a soma loss rate of 0.15±0.04 %/yr (average±SD). As expected, this rate is more consistent with loss due to normal aging (~0.5%/yr) than to glaucomatous progression (~4.6%/yr). Aside from these rare isolated losses, the GCL soma mosaic was highly stable over the one year interval examined. Our measurements of peak GCL soma density did not differ significantly from histology reported in the literature.
The inner retina is critical for visual processing, but much remains unknown about its neural circuitry and vulnerability to disease. A major bottleneck has been our inability to observe the structure and function of the cells composing these retinal layers in the living human eye. Here, we present a noninvasive method to observe both structural and functional information. Adaptive optics optical coherence tomography (AO-OCT) is used to resolve the inner retinal cells in all three dimensions and novel post processing algorithms are applied to extract structure and physiology down to the cellular level. AO-OCT captured the 3D mosaic of individual ganglion cell somas, retinal nerve fiber bundles of micron caliber, and microglial cells, all in exquisite detail. Time correlation analysis of the AO-OCT videos revealed notable temporal differences between the principal layers of the inner retina. The GC layer was more dynamic than the nerve fiber and inner plexiform layers. At the cellular level, we applied a customized correlation method to individual GCL somas, and found a mean time constant of activity of 0.57 s and spread of ±0.1 s suggesting a range of physiological dynamics even in the same cell type. Extending our method to slower dynamics (from minutes to one year), time-lapse imaging and temporal speckle contrast revealed appendage and soma motion of resting microglial cells at the retinal surface.
Absorption of light by photoreceptors initiates vision, but also leads to accumulation of toxic photo-oxidative
compounds in the photoreceptor outer segment (OS). To prevent this buildup, small packets of OS discs are
periodically pruned from the distal end of the OS, a process called disc shedding. Unfortunately dysfunction in
any part of the shedding event can lead to photoreceptor and RPE dystrophy, and has been implicated in
numerous retinal diseases, including age related macular degeneration and retinitis pigmentosa. While much is
known about the complex molecular and signaling pathways that underpin shedding, all of these advancements
have occurred in animal models using postmortem eyes. How these translate to the living retina and to humans
remain major obstacles. To that end, we have recently discovered the optical signature of cone OS disc shedding
in the living human retina, measured noninvasively using optical coherence tomography equipped with adaptive
optics in conjunction with post processing methods to track and monitor individual cones in 4D. In this study,
we improve on this method in several key areas: increasing image acquisition up to MHz A-scan rates,
improving reliability to detect disc shedding events, establishing system precision, and developing cone
tracking for use across the entire awake cycle. Thousands of cones were successfully imaged and tracked over
the 17 hour period in two healthy subjects. Shedding events were detected in 79.5% and 77.4% of the tracked
cones. Similar to previous animal studies, shedding prevalence exhibited a diurnal rhythm. But we were
surprised to find that for these two subjects shedding occurred across the entire day with broad, elevated
frequency in the morning and decreasing frequency as the day progressed. Consistent with this, traces of the
average cone OS length revealed shedding dominated in the morning and afternoon and renewal in the evening.
Retinal pigment epithelium (RPE) cells are vital to health of the outer retina, however, are often
compromised in ageing and ocular diseases that lead to blindness. Early manifestation of RPE disruption
occurs at the cellular level, but while in vivo biomarkers at this scale hold considerable promise, RPE
cells have proven extremely challenging to image in the living human eye. Recently we addressed this
problem by using organelle motility as a novel contrast agent to enhance the RPE cell in conjunction with
3D resolution of adaptive optics-optical coherence tomography (AO-OCT) to section the RPE layer. In
this study, we expand on the central novelty of our method – organelle motility – by characterizing the
dynamics of the motility in individual RPE cells, important because of its direct link to RPE physiology.
To do this, AO-OCT videos of the same retinal patch were acquired at approximately 1 min intervals or
less, time stamped, and registered in 3D with sub-cellular accuracy. Motility was quantified by an
exponential decay time constant, the time for motility to decorrelate the speckle field across an RPE cell.
In two normal subjects, we found the decay time constant to be just 3 seconds, thus indicating rapid
motility in normal RPE cells.