DOI: 10.5061/dryad.02v6wwqb2
title: Micron-resolution fiber mapping in histology independent of sample preparation

description: Mapping the brain's fiber network is crucial for understanding its
 function and malfunction, but resolving nerve trajectories over large
 fields of view is challenging. Electron microscopy only studies small
 brain volumes, diffusion magnetic resonance imaging (dMRI) has limited
 spatial resolution, and polarization microscopy provides unidirectional
 orientations in birefringence-preserving tissues. Scattered light imaging
 (SLI) has previously enabled micron-resolution mapping of
 multi-directional fibers in unstained brain cryo-sections. Here, we show
 that using a highly sensitive setup, computational SLI (ComSLI) can map
 fiber networks in histology independent of sample preparation, also in
 fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissues,
 including whole human brain sections. We showcase this method in new and
 archived, animal and human brain sections, for different stains and steps
 of sample preparation (in paraffin, deparaffinized, stained). Employing
 novel analyses, we convert microscopic orientations to
 microstructure-informed fiber orientation distributions (μFODs). Adapting
 MR tractography tools, we trace axonal trajectories via orientation
 distribution functions and microstructure-derived tractograms, revealing
 white and gray matter connectivity. These allow us to identify altered
 microstructure in multiple sclerosis and leukoencephalopathy, reveal
 deficient tracts in hippocampal sclerosis and Alzheimer's disease,
 and show key advantages over dMRI, polarization microscopy, and structure
 tensor analysis. Finally, we map fibers in non-brain tissues -including
 muscle, bone, and blood vessels- unveiling the tissue's function. Our
 cost-effective, versatile approach enables micron-resolution studies of
 intricate fiber networks across tissues, species, diseases, and sample
 preparations, offering new dimensions to neuroscientific and biomedical
 research.
description: Sample preparation Whole human brain
 (BigBrain) sections The silver-stained human brain
 section (Fig. 1, Supplementary Movie 1, and Supplementary Figs. 1, 2, and
 10) was obtained from a 30-year-old male body donor without neurological
 disorders. The brain was removed within 24 hours after death, fixed in 4%
 formalin, dehydrated in increasing alcohol series (80%, 90%, 96%, 100%
 ethanol for at least one week), and embedded in 57-60°C paraffin solution
 for two to three months. For a more detailed description, see Amunts et
 al., 2013<sup>11</sup>. Subsequently, the brain was coronally
 cut into 20 µm-thin sections from anterior to posterior with a large-scale
 microtome (Leica SM2500 Microtome) and mounted. The sections were placed
 in a decreasing alcohol series to remove the paraffin, stained with silver
 following the protocol of Merker<sup>62</sup> to highlight
 neuronal cell bodies, and mounted on glass slides. The sections are part
 of the so-called second <em>BigBrain</em> data
 set<sup>63</sup>, 3D-reconstructed with the same spatial
 resolution of 20μm isotropic, such as the original Jülich
 <em>BigBrain</em>s<sup>11</sup>. For our study, we
 used section no. 3452. The Cresyl-violet stained human
 brain sections (Fig. 4, and Supplementary Figs. 8, 9, and 11) were
 obtained from a 71-year-old male body donor without neurological
 disorders. The brain was prepared as described above, but stained with
 Cresyl-violet instead of silver. For our study, sections no. 3301 (Fig. 4,
 and Supplementary Figs. 8 and 9) and 2520 (Supplementary Fig. 11) were
 selected and measured one and a half years after tissue
 preparation. The body donors gave written informed
 consent for the general use of postmortem tissue in this study for the
 aims of research and education. The usage is covered by a vote of the
 ethics committee of the medical faculty of the Heinrich Heine University
 Düsseldorf, Germany (#4863). 120-year-old
 myelin-stained human brain section The myelin-stained
 human brain section (Fig. 2B) comes from the brain collection of the
 Cécile and Oskar Vogt Institute for Brain Research, Heinrich Heine
 University Düsseldorf, Germany. The brain of a 25-year-old male was
 embedded in celloidin and stained according to Weigert’s iron hematoxylin
 myelin staining in 1904<sup>64</sup>.
 Human hippocampus, cortex, and pathology FFPE brain
 sections Four-millimeter thick formalin-fixed human
 specimens were dehydrated in increasing ethanol steps (70% x2, 95% x2,
 100% x3, 3.5hrs each step), cleared in xylene (3.5hrs x2),
 paraffin-embedded (3.5hrs x2), and sectioned into 5µm-thin sections. The
 sections were de-waxed and stained with agents as indicated. The
 hippocampal sections in Fig. 2A and Supplementary Fig. 3 were from an
 89-year-old male with Alzheimer’s pathology, stained against microglia
 (CD163), Perl’s iron with Diaminobenzidine (DAB) enhancement, tau, and
 amyloid, with hematoxylin counterstain where indicated. Sections from
 brains with multiple sclerosis (80 years old, male, from temporal
 periventricular white matter and cortex) and leukoencephalopathy (43 years
 old, male, from periventricular white matter and cingulum) were stained
 with hematoxylin and eosin, luxol fast blue plus hematoxylin and eosin,
 and neurofilament (2F11) (Fig. 3 and Supplementary Figs. 5-6). Hippocampal
 and visual cortex sections in Supplementary Fig. 4 were from a 60-year-old
 male, stained with hematoxylin & eosin, and a 67-year-old female,
 stained with luxol fast blue, respectively. The sclerotic hippocampal
 section in Supplementary Fig. 7 was from a 69-year-old female with
 epilepsy, the control was from a 66-year-old female with no
 neuropathologic abnormality, and the AD tau-stained hippocampus was the
 same as in Fig. 2A, as described above. Specimens were acquired under
 Stanford ADRC IRB (Assurance nr. FWA00000935).
 Fresh-frozen human hippocampus and visual cortex
 sections The human hippocampus and primary visual
 cortex fresh-frozen sections (Supplementary Fig. 5) were from an
 88-year-old male with Lewy Body Disease, low Alzheimer’s disease
 pathology, and cerebrovascular dementia. The brain was processed according
 to Stanford ADRC procedures; after autopsy, it was cut into 5mm coronal
 slabs and frozen using frozen metal plates in dry ice. The specimens were
 excised from the frozen slab, and 30μm sections were cut using a cryostat.
 The sections were uncover-slipped and let thaw under the microscope, which
 happened in the first ~100 seconds given their thickness. Specimens were
 acquired under Stanford ADRC IRB (Assurance nr. FWA00000935).
 Mouse brain section A female ~10-week-old
 C57BL/6 mouse (Jackson Laboratories) was housed in a
 temperature-controlled environment, with a 12-hour light/dark schedule and
 <em>ad libitum</em> food/water access. It was euthanized for
 the purposes of a different study (APLAC #32577) under anesthesia with
 2-3% isoflurane followed by cardiac puncture and perfusion with 20 mL
 phosphate-buffered saline (PBS). The brain was harvested, kept in 4%
 paraformaldehyde (PFA) in PBS for 24 hours at 4°C, transferred to 10%,
 20%, and 30% sucrose in PBS, embedded in Tissue-Tek O.C.T. in dry ice for
 1 hour, and cut sagittally into 10μm sections using a cryotome (Leica
 CM1860). The sections were subsequently washed, mounted on a glass slide,
 incubated with Iba1 antibody (dilution 1:200), secondary antibody (goat
 anti-rabbit Cy3 1:200), and cover-slipped. A mid-sagittal section was
 selected for evaluation (Fig. 2G-J). Pig brain
 section A 4-week female Yorkshire pig (#2) was
 euthanized for a different study (Stanford APLAC protocol nr 33684), the
 brain was harvested, cut into 5-mm coronal slabs using a brain slicer, and
 a mid-frontal slab (#5) was paraffin-embedded, similar to the human
 pathologic specimen preparation above. The slab was cut in 10μm sections
 using a Leica HistoCore AUTOCUT microtome. After deparaffinization, a
 section (#127) was stained with hematoxylin and eosin and cover-slipped
 (Fig. 2K-N). Human tongue, colorectal, bone, and
 artery wall sections The non-brain tissue sections
 (Fig. 5 and Supplementary Fig. 12) were obtained from a tissue archive at
 Erasmus Medical Center, Rotterdam, the Netherlands, approved by the
 Medisch Ethische Toetsing Commissie (METC) under number MEC-2023-0587. The
 tissue samples were obtained from patients during surgery. The bone sample
 was decalcified first using DecalMATE by Milestone Medical. Afterwards,
 all samples were fixed in 4% formaldehyde for 24 hours, dehydrated in
 increasing alcohol series (70%, 80%, 90%, 96%, 100% ethanol), treated with
 xylene, embedded in paraffin, and cut with a microtome (Leica RM2165) into
 4μm-thin sections. The sections were placed in a decreasing alcohol series
 to remove the paraffin, mounted on glass slides, stained with hematoxylin
 and eosin (artery wall with Verhoeff-Van Gieson elastin staining), and
 then cover-slipped. Brightfield microscopy
 The whole human brain sections were scanned with the TissueScope
 LE120 Slide Scanner by Huron Digital Pathology, Huron Technologies
 International Inc. The device measures in brightfield mode with 20X
 magnification and 0.74 NA, providing a pixel size of 0.4µm. The final
 images were stored with a pixel size of 1µm. The
 hippocampus, cortex, pathology, and animal brain sections were scanned
 using an Aperio AT2 whole slide scanner with the ImageScope software and a
 20X magnification, resulting in brightfield images with a pixel size of
 0.5μm. The stained non-brain microscopy slides were
 scanned using the Nanozoomer 2.0 HT digital slide scanner by Hamamatsu
 Photonics K.K., offering a 20X magnification and a pixel size of 0.46µm.
 The unstained non-brain microscopy slides were scanned using the Keyence
 VHX-6000 Digital Microscope (with VH-ZST objective, 20X), with a pixel
 size of 10μm. ComSLI Whole human
 brain (silver-stained), hippocampus, cortex, pathology, and animal brain
 sections Measurements were performed with a rotating
 light source and camera (cf. Fig. 1B), using a Flexacam C3 12 MP
 microscope camera (Leica) and a Navitar 12X Zoom Lens with a 0.67X
 Standard Adapter and a 0.5X Lens Attachment, with 4.25-9μm pixel size, as
 indicated in the figure captions. As a light source, an ADJ Pinspot LED II
 was used, with a 5.1 cm diameter and 3.5° full-angle of divergence,
 oriented at ~45° with respect to the sample plane. A motorized specimen
 stage enabled the whole-human-brain section scanning in 8x5 tiles, all
 other brain sections were scanned at a single tile. Images were acquired
 at 10o rotation steps (36 images/sample) with 125ms exposure time, except
 for the sections in paraffin that gave very strong scattering and were
 imaged with 7ms exposure time. Prior to the measurement, a 100mm diameter
 diffuser plate (Thorlabs) was measured for calibration (see below for
 calibration details). Whole human brain
 (Cresyl-violet) and non-brain tissue sections
 Measurements were similarly performed with a rotating light
 source and camera (cf. Fig. 1B), using a fiber-coupled LED light source
 consisting of an ultra-high power LED (UHP-FB-W50 by Prizmatix) with
 400-750nm wavelength (peak at 443nm), 2-meter long step-index multimode
 silica (low OH) fiber patch cord (Thorlabs), a 25.4 mm diameter
 collimating optics (FCM1-0.5-CN by Prizmatix), and a 25.4 mm diameter
 engineered diffuser (beam shaper) for homogenizing the illumination
 (ED1-S20-MD by Thorlabs), yielding top-hat beam with 20° full-angle of
 divergence. The exposure time was adjusted manually per sample for
 maximizing the dynamic range of the captured signal while avoiding
 saturation (range: 50-100 ms). The light source was oriented at ~45° with
 respect to the sample and rotated with a motorized specimen stage (ZABER
 X-RSB060AD-E01-KX14A) in steps of 15° (24 images/sample). Images were
 taken with a 20 MP monochromatic CMOS camera (BASLER acA5472-17um) and a
 Rodenstock Apo-Rodagon-D120 Lens, yielding a pixel size of 3μm (4μm
 optical resolution) and a field-of-view of 16x11mm². A motorized specimen
 stage was used to perform whole-slide scanning. Prior to the measurement,
 a diffuser plate (DG100x100 N-BK7 ground glass diffuser, 1500 grit,
 Thorlabs) was measured for calibration. 120-year-old
 myelin-stained brain section The measurement was
 performed with a similar camera and lens as for the non-brain tissue
 sections (BASLER acA5472-17uc and Rodenstock Apo-Rodagon-D120), using an
 LED display instead of a focused light source (50x50
 cm<sup>2</sup>, 128x128 RGB-LEDs, Absen Polaris 3.9pro
 In/Outdoor LED Cabinet). The sample was illuminated by a green circle
 segment (9° azimuthal and polar widths, respectively) with an effective
 illumination angle of 47°, which was rotated in 15° steps. Images were
 taken with 10-second exposure time and a gain of 10, and 4 images were
 averaged per illumination angle to increase signal-to-noise.
 ComSLI image analysis Flat-field
 correction Prior to each measurement session, a
 diffuser plate was measured under similar conditions. A 100-pixel Gaussian
 blur was applied to diffuser images to homogenize defects. Subsequently,
 the blurred images of all angles were divided by the average of their
 maxima for normalization. These normalized diffuser images were used to
 calibrate the measured tissue images, aiming to account for the uneven
 illumination across the field of view for each image: Each tissue image
 was divided by its corresponding normalized diffuser image of the same
 illumination angle. Generation of fiber orientation
 and vector maps Each calibrated image series from a
 ComSLI measurement was evaluated with the open-source software
 SLIX<sup>34</sup>, which analyzes the position of scattering
 peaks to compute the fiber orientations and visualize them in
 color-encoded maps, using multi-colored pixels and colored vector lines.
 Measurements with 15° azimuthal steps were processed without filtering.
 Measurements with 10° azimuthal steps were processed with a Fourier
 low-pass filter (40% cutoff frequency, 0.225 window width) before
 generating the parameter maps, as described in
 <sup>22</sup>. Microstructure-derived
 fiber orientation distributions (μFODs) To calculate
 and plot the μFODs, the ComSLI fiber orientation map was partitioned into
 pixel kernels depending on the intended μFOD resolution. For instance, for
 a ComSLI dataset with pixel size of 7μm and intended μFOD resolutions of
 ~50 or ~500μm, a 7x7 or 71x71 pixel kernel was used respectively (Fig.
 1H). Similarly, to calculate μFODs for specific regions of interest, e.g.,
 the lesions in pathology (Fig. 3), orientations of all pixels in the area
 were considered. All fiber orientations of all pixels within each kernel
 or area of interest were then rendered as a polar histogram in 20 bins of
 9°, covering 0° -180°, and mirrored to 180° -360°. To create a continuous
 polar function representing the μFOD, the mid-points of the bins were
 fitted by a spline, which was then rendered as a polar plot (Fig. 1H, Fig.
 3D, G, X, Fig. 4C, D, Fig. 5C, G, L, O). Diffusion
 MR-based orientation distribution functions (ODFs) and
 tractography To generate ODFs and enable tractography,
 we opted for using existing tools developed in MR tractography, given the
 advanced and widely tested algorithms used in the field. To achieve that,
 an artificial diffusion MRI dataset was created based on the ComSLI μFODs
 described above. The dataset included 3 b=0ms/μm<sup>2</sup>
 and 60 b=1ms/μm<sup>2</sup> volumes. The 3
 b=0ms/μm<sup>2</sup> volumes had a value of 1 at all voxels.
 The 60 b=1ms/μm<sup>2</sup> volumes consisted of 3 sets:
 <strong>i</strong>) The first 20 were derived for the 20
 in-plane orientations of the μFOD angles (20 angles, 9° apart, covering
 180°), see above. There, the signal for each angle was calculated for
 every pixel as , where <em>n</em> is the frequency
 of fiber orientations for that angle in that pixel, based on the μFOD
 polar histogram.  <strong>ii</strong>) The second 20
 orientations were at the plane perpendicular to the plane of the section.
 For these, the signal was set to 1 for all pixels, indicating no signal
 loss and hence no axons along that plane, thus enforcing the orientations
 to be within the section plane. <strong>iii</strong>) The
 third set of 20 orientations was the initial set of 20 polar histogram
 orientations but tilted 20° off the section plane towards the
 perpendicular plane. There, each pixel’s signal was , where
 <em>Signal<sub>0</sub></em> is the signal of the
 first set of angles. This aimed to approximate a diffusion MRI signal and
 fiber distribution off-plane, where the signal loss at 20° off the
 detected in-plane axon orientation is 20% of the signal loss along the
 axons.  To compute the ODFs and tractograms,
 <em>MRtrix3</em><sup>35</sup> functions were used
 with the generated artificial MRI signal along with the corresponding bval
 and bvec files as input: <em>dwi2response</em> with the
 <em>fa</em> algorithm and l<sub>max</sub>=6 to
 calculate the fiber response and <em>dwi2fod</em> with the
 <em>csd</em> algorithm and l<sub>max</sub>=6 to
 calculate the ODFs. Finally, the <em>tckgen</em> function was
 used to generate tractograms, with a minimum tract length of 2mm, which
 was found to be reasonable to compute given the micron-scale pixel
 sizes. Nissl-ST The fiber
 orientation maps were computed in Matlab following the procedure described
 and code shared by Schurr & Mezer<sup>25</sup>, using
 default settings and 100μm as a kernel to compute the structure tensor
 (effective resolution). ComSLI – Histology
 registration To enable quantitative, pixel-wise
 comparison between ComSLI and Nissl-ST outputs (Fig. 4 and Supplementary
 Figs. 10-11) as well as quantification of the ComSLI and histology stain
 intensities (Fig. 3 and Supplementary Fig. 6), the histology images were
 linearly 2D-registered to the corresponding ComSLI average scattering
 images of the same section using the <em>antsRegistration</em>
 function in <em>ANTs</em><sup>65</sup> (options:
 <em>--transform Similarity[0.1], --convergence [100 x 70 x 50 x
 0,1e-6,10] --smoothing-sigmas 3x2x1x0vox --shrink-factors
 8x4x2x1</em>). To register consecutive histology
 sections (Figs. 2, 3, and Supplementary Fig. 6) the
 <em>SyN</em> transform of the same <em>ANTs</em>
 command was used (options: <em>--transform SyN[0.1,3,0]
 --convergence [800 x 400 x 200 x 100 x 70 x 50 x 0,1e-6,10]
 --smoothing-sigmas 15x9x5x3x2x1x0vox --shrink-factors
 64x32x16x8x4x2x1</em>). 3D-PLI
 The 3D-PLI measurements were performed using the LMP3D microscope
 (Taorad GmbH, Germany), containing an evo4070MFLGEC (2048x2048) camera and
 a Nikon 4x (NA 0.2) lens, which achieves a pixel size of 1.85μm and an
 in-plane optical resolution of 2.2μm (determined by US-Airforce target).
 The sample was illuminated by linearly polarized light at 20° rotation
 angles and analyzed by a circular analyzer as described by Axer et
 al.<sup>19</sup>. 3D-PLI FOM was computed on the supercomputer
 JURECA at Forschungszentrum Jülich (grant no. 28954).
 Diffusion MRI The diffusion MRI
 dataset<sup>30</sup> is from a 30-year-old male who underwent
 18 hours of diffusion MRI scanning in the MGH-USC 3T Connectom scanner
 using gSlider-SMS<sup>66</sup>. After manually identifying the
 MR plane that most closely matched the <em>BigBrain</em>
 histology sections, the entire dataset was rotated using FreeSurfer’s
 <em>freeview</em> and the b-vectors were rotated at the same
 angles (rotation angles for the Silver-stained section were -34° sagittal
 and 1.5° axial, for the Cresyl-violet -30.4° sagittal). Fiber responses
 and orientation distributions were computed using the
 <em>dwi2response</em> and <em>dwi2fod</em>
 functions in <em>MRtrix3</em><sup>35</sup>, using
 the multi-tissue, multi-shell algorithm<sup>38</sup>, and
 visualized in <em>mrview</em>. To generate whole-brain
 colormaps in Fig. 4 and Supplementary Fig. 10,
 <em>MRtrix3</em>’s <em>sh2amp</em> function was
 used to probe fiber orientations at the coronal plane at 5° intervals, and
 colormaps were generated using SLIX<sup>34</sup>.
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description: # Micron-resolution fiber mapping in histology independent of sample
 preparation
 [https://doi.org/10.5061/dryad.02v6wwqb2](https://doi.org/10.5061/dryad.02v6wwqb2) This dataset includes raw figures and data presented in the manuscript "*Micron-resolution fiber mapping in histology independent of sample preparation*". [https://www.biorxiv.org/content/10.1101/2024.03.26.586745](https://www.biorxiv.org/content/10.1101/2024.03.26.586745)  #### Version changes The Dryad dataset is updated to reflect the data of the study as presented in the latest version of the article in bioRxiv. *2025-03-26*: Multiple new datasets corresponding to new figures, figure panels, and quantitative analyses were added, pertaining to quantitative ComSLI/Nissl-ST pixelwise comparisons, new microstructure-derived fiber orientation distributions (μFODs), tractography results from ComSLI data, scripts for generating virtual MRI dataset to enable tractography, and analysis of fresh-frozen samples. The files are not only tarred but also gzipped, which brought down the size considerably. ## Description of the data and file structure Each file is named according to the Figure number in which it is presented in the manuscript. Figure_SX refers to supplementary figures. All brain image files are in .tiff or .nii format, and Nissl-ST data are in Matlab .mat files. Scripts are also provided for the conversion of ComSLI data to microstructure-informed fiber orientation distributions (μFODs), to a virtual MR dataset, and subsequent orientation distribution functions and tracts using MRtrix3. For questions or requests, please contact Marios Georgiadis (email: [mariosg@stanford.edu](mailto:mariosg@stanford.edu)) and Miriam Menzel (email: [m.menzel@tudelft.nl](mailto:m.menzel@tudelft.nl))