DOI: 10.5061/dryad.95x69p8th
title: Quantifying the influence of optical coherence tomography beam tilt in the normal adult mouse retina

description: Parallel microstructures within the retina – like retinal nerve fiber
 layer (RNFL) axons – differentially reflect light depending on its angle.
 This effect has previously been observed with optical coherence tomography
 (OCT), but it is under-studied. Quantification of this effect might
 provide useful information about retinal microstructures, and therefore
 the broader health of the retina. Our goal was to quantify the influence
 OCT beam tilt on reflectivity of each layer of the normal adult mouse
 retina.
description: Using a Bioptigen Envisu UHR2200 system, we collected OCT images
 of twenty-seven healthy control mouse retinas (from fifteen mice). Images
 included the optic nerve head, the temporal retina, and the nasal retina.
 We converted signal intensities to estimated attenuation coefficients
 (eAC) for further processing.  Each retina was imaged multiple times with
 various beam tilts. eAC was measured at beam tilts in the range of ±30°
 (where 0° would be the most standard acquisition, where the beam is
 perpendicular to the surface of the retina). Images had a nominal
 resolution of 1.4 µm × 1.4 µm. Retinas were digitally linearized and
 spatially normalized to facilitate averaging and data aggregation across
 mice. This repository includes all retinal images processed for the
 associated publication. For three of the retinas, we also provide R code
 (r-project.org) and images from intermediate processing steps.
description: # Quantifying the influence of optical coherence tomography beam tilt in
 the normal adult mouse retina.
 [https://doi.org/10.5061/dryad.95x69p8th](https://doi.org/10.5061/dryad.95x69p8th) ## Description of the data and file structure In optical coherence tomography (OCT), the angle of the beam influences the apparent reflectivity of the retina. The relationship between beam tilt and reflectivity has been characterized in some layers of the mouse retina. We sought to characterize that relationship for all layers of the retina. To this end, we collected multiple OCT images at varying beam tilts from fifteen (15) adult wild-type C57 mice (Jackson Labs, Bar Harbor, ME, age ~3 mo). References: Meleppat RK, Zhang P, Ju MJ, Manna SK, Jian Y, Pugh EN, Zawadzki RJ, 2019. Directional optical coherence tomography reveals melanin concentration-dependent scattering properties of retinal pigment epithelium. J Biomed Opt 24(6):1-10. ### Files and variables #### File: beam\_tilt\_data\_for\_Dryad.zip **Description:** Each folder contains images from a unique eye. The folder name identifies the mouse by its assigned number (e.g., 718) and whether the images are from the left eye ("OS") or right eye ("OD"). The original images are organized as a stack (or "volume") and stored in the Analyze image format (which uses .img/.hdr files). Analyze images are most easily viewed with ImageJ. All folders contain: 1.    The original images of the retina, with files names name identical to the folder name. 2.    Images of the retina after some processing (including calculation of estimated attenuation coefficients, cropping, resizing), with a suffix of "_log10attR". 3.    Fully processed and spatially normalized images of the retina, with a suffix of "_RAS". 4.    An .Rdata file generated at the end of processing. 5.    A .txt file showing average retinal thicknesses, also generated at the end of processing. Three folders (folder names ending in "_processing_example") contain additional files to show intermediate processing steps. Folders containing data from the left eye contain another file ("*orig*" prefix) explained in the next section. ## Code/software Images of wild type mouse retinas were collected on a Bioptigen Envisu UHR2200 system, exported, then saved in the Analyze image format. This is the general procedure for processing the images (done with R version 4.0.5 and ImageJ version 1.53e): 1.    Horizontally flip images from the left eye (OS). This simplifies later tracking of nasal versus temporal retina. In this repository, \_orig\_ is added as a prefix to the original (not-yet-flipped) files. 2.    Run \_estimated_ATTEN_COEF_8bitMouse_2024-03MAR-25.R. You will have to update the line of code that describes the filename of the image. The resulting file will have a \_log10attenuation suffix. Pixel values are estimated attenuation coefficients (eAC). In the manuscript, eAC is reported in m^-1 and log-transformed. Here, it is stored in mm^-1 and log-transformed. (Adding 3 to each pixel value would convert from mm^-1 to m^-1.) 3.    Load that \_log10attenuation file into ImageJ. The original pixel sizes are 1.4 µm/pixel in the horizontal (transverse; nasal↔temporal) direction, and 1.53 µm/pixel in the vertical (axial; vitreous↔choroid) direction. Resizing the image in the vertical (axial) direction by x1.093 (from 1024 to 1119) results in a nominal resolution of 1.4 µm × 1.4 µm. We do not use interpolation. At this stage of processing, we were cautious about “averaging” any unusually low pixel values (e.g., eAC’s below -3 mm^-1) with neighboring values through interpolation. Crop the resized image and save with the “_log10attR” suffix. 4.    In ImageJ, use a copy of that \_log10attR image to label structures in the retina. Threshold the image as needed to maximize visibility, then convert the image to 8bit. Set the maximum pixel value to 240: Values above 240 are then used to mark different structures. Now, use the segmented line tool and color picker, to mark the following in all images: a.    The relatively dark (low eAC) band just exterior to the retinal pigment epithelium (RPE) should be labeled with pixel values of 255. If you read the R code, this is often casually described as the basement membrane, but based on comparisons of low- versus high-melanin mice (e.g., doi: 10.1073/pnas.1620572114) this is likely choriocapillaris (CC) instead of basement membrane. b.    Pixel values of 254 at the external limiting membrane. c.     Pixel values of 253 at the ONL-OPL border. d.    Pixel values of 252 at the INL-IPL border. e.    Pixel values of 250 at the GCL-RNFL border. f.      Pixel values of 249 at the RNFL-vitreous border. g.    A line of pixel values of 243 should mark the optic nerve head. Save this labeled image with a \_MARKED suffix. 5.    Run \_MOUSE_OCT_ANGLES_for_attR_draw255inCC_labelALLslices_2024-03MAR-25.R. (Regarding the filename: Older versions of the code permitted drawing the 255 line on the RPE instead of exterior to it, and/or permitted steps 4b-4f on only the first image, instead of *all* slices. In the latter – which was used to process 554_OD and 553_OD, among others – the lack of user control at defining borders sometimes required censoring structures interior to the retina (e.g., vasculature).) The result should be: a.    A flattened image (with the suffix “_linearized”). b.    A spatially-normalized version of the flattened image. This *must* be inspected. If it looks good, then the program ran successfully. If it doesn’t look good, then the flattened image may help you troubleshoot. c.     A .txt file with image thicknesses. d.    An .Rdata file with the suffix “_done”, to be used later.