Imaging complex, non-planar anatomies with optical coherence tomography (OCT) is limited by the optical field of view (FOV) in a single volumetric acquisition. Combining linear mechanical translation with OCT extends the FOV but suffers from inflexibility in imaging non-planar anatomies. We report the robotic OCT to fill this gap. To address challenges in volumetric reconstruction associated with the robotic movement accuracy being two orders of magnitudes worse than OCT imaging resolution, we developed a volumetric montaging algorithm. To test the robotic OCT, we imaged the entire circumferential aqueous humor outflow pathway, whose imaging has the potential to customize glaucoma surgeries but is typically constrained by the FOV in mice in vivo. We acquired volumetric OCT data at different robotic poses and reconstructed the entire anterior segment of the eye. From the segmented Schlemm's canal volume, we showed its circumferentially heterogeneous morphology; we also revealed a segmental nature in the circumferential distribution of collector channels with spatial features as small as a few micrometers.

We seek to develop techniques for high-resolution imaging of the tree shrew retina for visualizing and parameterizing retinal ganglion cell (RGC) axon bundles in vivo. We applied visible-light optical coherence tomography fibergraphy (vis-OCTF) and temporal speckle averaging (TSA) to visualize individual RGC axon bundles in the tree shrew retina. For the first time, we quantified individual RGC bundle width, height, and cross-sectional area and applied vis-OCT angiography (vis-OCTA) to visualize the retinal microvasculature in tree shrews. Throughout the retina, as the distance from the optic nerve head (ONH) increased from 0.5 mm to 2.5 mm, bundle width increased by 30%, height decreased by 67%, and cross-sectional area decreased by 36%. We also showed that axon bundles become vertically elongated as they converge toward the ONH. Ex vivo confocal microscopy of retinal flat-mounts immunostained with Tuj1 confirmed our in vivo vis-OCTF findings.

Increases in speed and sensitivity enabled rapid clinical adoption of optical coherence tomography (OCT) in ophthalmology. Recently, visible-light OCT (vis-OCT) achieved ultrahigh axial resolution, improved tissue contrast, and provided new functional imaging capabilities, demonstrating the potential to improve clinical care further. However, limited speed and sensitivity caused by the high relative intensity noise (RIN) in supercontinuum lasers impeded the clinical adoption of vis-OCT. To overcome these limitations, we developed balanced-detection vis-OCT (BD-vis-OCT), which uses two calibrated spectrometers to cancel RIN and other noises. We analyzed the RIN to achieve robust subpixel calibration between the two spectrometers and showed that BD-vis-OCT reduced the A-line noise floor by up to 20.5 dB. Metrics comparing signal-to-noise-ratios showed similar image qualities across multiple reference arm powers, a hallmark of operation near the shot-noise limit. We imaged healthy human retinas at an A-line rate of 125 kHz and a field-of-view up to 10 mm ×4 mm. We found that BD-vis-OCT revealed retinal anatomical features previously obscured by the noise floor.

SUMMARY: Spectroscopic single-molecule localization microscopy (sSMLM) simultaneously captures the spatial locations and full spectra of stochastically emitting fluorescent single molecules. It provides an optical platform to develop new multimolecular and functional imaging capabilities. While several open-source software suites provide subdiffraction localization of fluorescent molecules, software suites for spectroscopic analysis of sSMLM data remain unavailable. RainbowSTORM is an open-source ImageJ/FIJI plug-in for end-to-end spectroscopic analysis and visualization for sSMLM images. RainbowSTORM allows users to calibrate, preview and quantitatively analyze emission spectra acquired using different reported sSMLM system designs and fluorescent labels. AVAILABILITY AND IMPLEMENTATION: RainbowSTORM is a java plug-in for ImageJ (https://imagej.net)/FIJI (http://fiji.sc) freely available through: https://github.com/FOIL-NU/RainbowSTORM. RainbowSTORM has been tested with Windows and Mac operating systems and ImageJ/FIJI version 1.52. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.