Imaging and quantifying ganglion cells and other transparent neurons in the living human retina Zhuolin Liua,1, Kazuhiro Kurokawaa, Furu Zhanga, John J. Leeb, and Donald T. Millera aSchool of Optometry, Indiana University, Bloomington, IN 47405; and bPurdue School of Engineering and Technology, Indiana University–Purdue University Indianapolis, Indianapolis, IN 46202 Edited by David R. Williams, University of Rochester, Rochester, NY, and approved October 18, 2017 (received for review June 30, 2017) Ganglion cells (GCs) are fundamental to retinal neural circuitry, apoptotic GCs tagged with an intravenously administered fluores- processing photoreceptor signals for transmission to the brain via cent marker (14), thus providing direct monitoring of GC loss. The their axons. However, much remains unknown about their role in second incorporated adaptive optics (AO)—which corrects ocular vision and their vulnerability to disease leading to blindness. A aberrations—into SLO sensitive to multiply-scattered light (12). major bottleneck has been our inability to observe GCs and their This clever combination permitted imaging of a monolayer of GC degeneration in the living human eye. Despite two decades of layer (GCL) somas in areas with little or no overlying nerve fiber development of optical technologies to image cells in the living layer (NFL) (see figure 5, human result of Rossi et al.; ref. 12). By human retina, GCs remain elusive due to their high optical trans- contrast, our approach uses singly scattered light and produces lucency. Failure of conventional imaging—using predominately sin- images of unprecedented clarity of translucent retinal tissue. This gly scattered light—to reveal GCs has led to a focus on multiply- permits morphometry of GCL somas across the living human ret- scattered, fluorescence, two-photon, and phase imaging techniques ina. We overcome the aforementioned obstacles by combining AO to enhance GC contrast. Here, we show that singly scattered light and OCT (AO-OCT) (15) to achieve high lateral and axial reso- actually carries substantial information that reveals GC somas, lution and high sensitivity, using 3D subcellular image registration axons, and other retinal neurons and permits their quantitative to correct eye motion, and using organelle motility inside GCL analysis. We perform morphometry on GC layer somas, including somas to increase cell contrast (16, 17). This imaging modality projection of GCs onto photoreceptors and identification of the enables light microscopy of the living human retina, a tool for fundamental studies linking anatomical structure with visual func- primary GC subtypes, even beneath nerve fibers. We obtained sin- – gly scattered images by: (i) marrying adaptive optics to optical tion (18 21). High-resolution images of retinal neurons in living coherence tomography to avoid optical blurring of the eye; (ii)per- eyes also promise improved diagnosis and treatment monitoring of GC and axonal loss in diseases of the optic nerve such as glaucoma forming 3D subcellular image registration to avoid motion blur; and (3, 4, 22, 23) and other neurodegenerative disorders such as Alz- (iii) using organelle motility inside somas as an intrinsic contrast heimer’s disease, Parkinson’s disease, and multiple sclerosis (24). agent. Moreover, through-focus imaging offers the potential to The 3D resolution of our AO-OCT method was 2.4 × 2.4 × 4.7 μm3 spatially map individual GCs to underlying amacrine, bipolar, hori- (width × length × depth), sufficient to resolve GCL somas in any zontal, photoreceptor, and retinal pigment epithelium cells, thus dimension. We acquired 1.5° × 1.5° AO-OCT volume images along exposing the anatomical substrate for neural processing of visual the horizontal meridian of the macula from four subjects free of ocular MEDICAL SCIENCES information. This imaging modality is also a tool for improving disease. AO-OCT videos were acquired at each retinal location with clinical diagnosis and assessing treatment of retinal disease. the system focused precisely at the GCL. In postprocessing, volumes were registered and averaged, and GCL somas were identified. adaptive optics | optical coherence tomography | organelle motility | This report is based on a total count of over 42,000 GCL retinal ganglion cells | retina somas at 26 different locations in the four subjects. The 3D he retina is an inverted stack of neurons requiring light to Significance ENGINEERING Ttraverse its full thickness before being absorbed by photore- ceptors to initiate vision (1). Retinal neurons anterior to photo- Ganglion cells are the primary building block of retinal neural — — receptors including ganglion cells (GCs) are therefore nearly circuitry, but have been elusive to observe and quantify in the transparent and well index matched to surrounding cells. These living human eye. Here, we show a light microscopy modality that properties, combined with tight packing of the GCs, ocular blur, reveals not only the somas of these cells, but also their 3D packing and retina motion, make these neurons extremely challenging to geometry, primary subtypes, and spatial projection to other image in the living human eye (2–4). Ex vivo studies overcome neurons. The method provides a glimpse of the rich tapestry of these by removing the retina and using stains and fluorescent neurons, glia, and blood vessels that compose the retina, thus markers (5–7), two-photon excitation (8, 9), differential in- exposing the anatomical substrate for neural processing of visual terference contrast optics (10), and extreme 3D resolution (11) to information. Clinically, high-resolution images of retinal neurons enhance contrast. Recently, some of these powerful methods have in living eyes hold promise for improved diagnosis and assessing been applied successfully to animals in vivo as, for example, two- treatment of ganglion cell and other neuron loss in retinal disease. photon excitation (12), but work remains to translate them to human. However, standard methods of imaging the human retina Author contributions: Z.L. and D.T.M. conceived and designed the project; Z.L., K.K., and in vivo—including fundus photography, scanning laser ophthal- J.J.L. developed image reconstruction, processing, and registration tools; Z.L. contributed — new analytic tools, Z.L., K.K., and F.Z. performed the experiments, Z.L., K.K., F.Z., and D.T.M. moscopy (SLO), and optical coherence tomography (OCT) fail analyzed the results; Z.L. and D.T.M. wrote the paper and all authors contributed to to visualize GCs and the other transparent neurons due to in- revisions; and D.T.M. supervised the project. sufficient resolution, axial sectioning, cell contrast, and correction The authors declare no conflict of interest. of eye motion artifacts. Indirect methods of inferring neuron This article is a PNAS Direct Submission. populations from bulk measures of retinal layer thicknesses and This open access article is distributed under Creative Commons Attribution-NonCommercial- clinical visual field testing can circumvent these problems, but NoDerivatives License 4.0 (CC BY-NC-ND). concerns about reliability remain (13). 1To whom correspondence should be addressed. Email: [email protected]. Two recent advances in SLO have shown promise for ob- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. serving GCs in the living human eye. One used SLO to detect 1073/pnas.1711734114/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1711734114 PNAS | November 28, 2017 | vol. 114 | no. 48 | 12803–12808 Downloaded by guest on September 26, 2021 spatial coordinates of the GCL soma centers were marked and provide detailed views of many retinal features of interest, such as used to quantify: soma stack thickness, diameter, reflectance, presumptive astrocytes or microglia at the ILM (Fig. 2D), GC axon density, and distribution of primary GC subtypes and GC pro- bundles of various calibers (Fig. 2E), the mosaic of GCL somas of jection onto cone photoreceptors (Materials and Methods). different characteristic sizes indicating different functional classes (Fig. 2F), and the dense mesh of dendrites and synapses between Results and Discussion GCs, amacrine cells, and bipolar cells in the IPL (Fig. 2G). To- Averaging and Registering AO-OCT Volumes. Imaging with coherent gether, these images provide a glimpse of the rich tapestry of light produces speckle that contains both noise and object in- neurons, glia, and blood vessels that can be appreciated by in- formation (e.g., soma shape) (25), the former preventing observa- teractive inspection of the imaged volume. tion of the latter (see example in Fig. 1; n = 1). Organelle motion in thesomacausesthenoisetochange from image to image, while the GCL Soma Size and Stack Thickness. We inspected the GCL of object information (soma) remains constant from image to image, recorded retinal volumes to estimate the size and layering of GCL assuming the images are registered to each other with an accuracy somas at different retinal eccentricities. Example images (Fig. 3 better than the size of individual somas. Therefore, averaging of and Fig. S1) clearly reveal the retinal gradient of soma size for all images reduces speckle noise while retaining soma information. We four subjects. The high axial resolution of our AO-OCT enables found empirically that averaging 100–160 registered AO-OCT visualization of the layering of GCL somas in depth, necessary for volumes of the same retinal patch improved signal-to-noise ratio measurements of cell density and observations of the arrangement and image contrast, dramatically improving the clarity of individual of somas in gaps between nerve fiber bundles and around blood GCL somas (see example in Fig. 1; n = 137). We quantified the vessels extending through the entire GCL (Figs. S2 and S3 and – – image enhancement due to motion of organelles inside somas and Movie S2). Stack thickness reached a maximum of 4 5 somas at 3 our ability to register to subcellular accuracy using a soma contrast 4.5° retinal eccentricity, decreasing rapidly toward the fovea and Materials and Methods slowly away from it to a minimum thickness of 1.