DOI: 10.5061/dryad.pzgmsbctz
title: Data retrieval from archival renal biopsies using nonlinear microscopy

description: Thorough examination of renal biopsies may improve understanding of renal
 disease. Imaging of renal biopsies with fluorescence nonlinear microscopy
 (NLM) and optical clearing enables three-dimensional (3D) visualization of
 pathology without microtome sectioning. Archival renal paraffin blocks
 from 12 patients were deparaffinized and stained with Hoechst and Eosin
 for fluorescent nuclear and cytoplasmic/stromal contrast, then optically
 cleared using benzyl alcohol benzyl benzoate (BABB). NLM images of entire
 biopsy fragments (thickness range 88-660 µm) were acquired using NLM with
 fluorescent signals mapped to an H&E color scale. Cysts,
 glomeruli, exudative lesions, and Kimmelstiel-Wilson nodules were
 segmented in 3D and their volumes, diameters, and percent composition
 could be obtained. The glomerular count on 3D NLM volumes was high
 indicating that archival blocks could be a vast tissue resource to enable
 larger-scale retrospective studies. Rapid optical clearing and NLM imaging
 enables more thorough biopsy examination and is a promising technique for
 analysis of archival paraffin blocks.
description: Archival renal biopsy paraffin blocks were collected. Specimens
 were deparaffinized, optically cleared, and stained with Hoechst 33342 and
 eosin Y. Stained specimens were digitized in 3D with dual-channel
 two-photon excitation fluorescence microscopy and sequential tiling in
 XYZ. See Materials and Methods for more detailed
 protocol information.
description: # Image datasets accompanying "Data retrieval from archival renal
 biopsies using nonlinear microscopy"
 The submission contains
 all source fluorescence microscopy datasets used to produce figures for
 the manuscript entitled, "Data retrieval from archival renal biopsies
 using nonlinear microscopy" PLOS ONE (Cahill et al., 2024). The
 source files are streams of 2D tiles, which when stitched together, form
 3D microscopic representations of archival renal biopsies. For
 convenience, we have also included pre-stitched, full-resolution & bit
 depth, 2-channel stacks. **Dataset name: Manuscript figure number:
 Description** LC-6-2: Figure 1: Image of a biopsy from a patient with
 advanced diabetic nephropathy. LC-7-2-rdo2: Figures 3 & 4: Image of a
 biopsy showing focal and segmental glomerulosclerosis with features of
 collapsing glomerulopathy LC-9-1-rdo: Figure 5: Image of a biopsy showing
 crescentic IgA nephropathy. LC-10-1: Figure 2: Image of a biopsy from a
 patient diagnosed with diabetic nephropathy and IgA nephropathy.
 LC-11-2-rdo: Figure 6: Image of a biopsy showing tubular necrosis.
 LC-13-1: Figure 10: Image of a biopsy from a patient diagnosed with
 lithium nephropathy. ## Description of the data and file structure Each
 dataset contains a stream of tiles and a pre-stitched 3D stack. Both files
 are OME-TIFF hyperstacks. Image tiles have dimensions 2×1024×1024
 (Channels×Height×Width) and are encoded in 16 bit unsigned integers. The
 time axis/dimension is used to represent tile index. The tiles are
 acquired in a boustrophedon pattern to span the entire specimen area.
 Stitched hyperstacks have dimensions Z×2×Y×X, where Z is the total number
 of slices (depths) acquired, Y is the total number of pixels in height,
 and X is total number of pixels width. Pixel spacing information is
 included in the image metadata. The channel order is eosin followed by
 Hoechst. ## Code/Software Both hyperstacks can be opened with ImageJ/Fiji
 using "Import"-&gt;"Bio-Formats" and selecting
 "View stack with:" "Hyperstack". Depending on your
 system memory and the hyperstack file size, you may also need to check
 "Use virtual stack". In composite color mode, eosin should
 appear as the red channel and Hoechst should appear as the green channel.
 Alternatively, datasets can be opened in programmatic languages, for
 instance in Python with the
 [tifffile](https://github.com/cgohlke/tifffile) package. Images can be
 recolored to emulate the appearance of hematoxylin-eosin stain under
 brightfield illumination using [previously published
 algorithms](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0159337).