Name: utilizing 3d printing technology to merge mri with histology: a protocol for brain sectioning
Uploaded: 2016-12-06T13:00:00
Duration: 15 min 53 s
Description: Watch this Scientific Journal Video about Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning at JoVE.com

The Intramural Research Program of NINDS supported this study. We thank the NIH Functional Magnetic Resonance Imaging Facility. We thank Jennifer Lefeuvre and Cecil Chern-Chyi Yen for assistance with postmortem MRI acquisition. We thank John Ostuni and the Section on Instrumentation Core Facility for assistance with 3D printing. Figure 1 of this work used snapshots from MeshLab, a tool developed with the support of the 3D-CoForm project.

<ol>
	<li>Evans, A. C., Frank, J. A., Antel, J., Miller, D. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+MRI+in+clinical+trials+of+multiple+sclerosis:+comparison+of+image+processing+techniques.">The role of MRI in clinical trials of multiple sclerosis: comparison of image processing techniques.</a> Ann Neurol. 41 (1), 125-132 (1997).</li><li>'t Hart, B. A., van Kooyk, Y., Geurts, J. J. G., Gran, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+primate+autoimmune+encephalomyelitis+model;+a+bridge+between+mouse+and+man.">The primate autoimmune encephalomyelitis model; a bridge between mouse and man.</a> Ann Clin Transl Neurol. 2 (5), 581-593 (2015).</li><li>Ontaneda, D., Hyland, M., Cohen, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+sclerosis:+new+insights+in+pathogenesis+and+novel+therapeutics.">Multiple sclerosis: new insights in pathogenesis and novel therapeutics.</a> Annu Rev Med. 63, 389-404 (2012).</li><li>Guy, J. R., Sati, P., Leibovitch, E., Jacobson, S., Silva, A. C., Reich, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Custom+fit+3D-printed+brain+holders+for+comparison+of+histology+with+MRI+in+marmosets.">Custom fit 3D-printed brain holders for comparison of histology with MRI in marmosets.</a> J Neurosci Methods. 257, 55-63 (2016).</li><li>Breen, M. S., Lazebnik, R. S., Wilson, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+registration+of+magnetic+resonance+image+data+to+histological+sections+with+model-based+evaluation.">Three-dimensional registration of magnetic resonance image data to histological sections with model-based evaluation.</a> Ann Biomed Eng. 33 (8), 1100-1112 (2005).</li><li>Dauguet, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+reconstruction+of+stained+histological+slices+and+3D+non-linear+registration+with+in-vivo+MRI+for+whole+baboon+brain.">Three-dimensional reconstruction of stained histological slices and 3D non-linear registration with in-vivo MRI for whole baboon brain.</a> J Neurosci Methods. 164 (1), 191-204 (2007).</li><li>McGrath, D. M., Vlad, R. M., Foltz, W. D., Brock, K. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Technical+note:+fiducial+markers+for+correlation+of+whole-specimen+histopathology+with+MR+imaging+at+7+tesla.">Technical note: fiducial markers for correlation of whole-specimen histopathology with MR imaging at 7 tesla.</a> Med Phys. 37, 2321-2328 (2010).</li><li>Schormann, T., Zilles, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-Dimensional+linear+and+nonlinear+transformations:+An+integration+of+light+microscopical+and+MRI+data.">Three-Dimensional linear and nonlinear transformations: An integration of light microscopical and MRI data.</a> Hum Brain Mapp. 6, 339-347 (1998).</li><li>Jiang, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combined+MR,+fluorescence+and+histology+imaging+strategy+in+a+human+breast+tumor+xenograft+model.">Combined MR, fluorescence and histology imaging strategy in a human breast tumor xenograft model.</a> NMR Biomed. 26 (3), 285-298 (2013).</li><li>Absinta, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Postmortem+magnetic+resonance+imaging+to+guide+the+pathologic+cut:+individualized,+3-dimensionally+printed+cutting+boxes+for+fixed+brains.">Postmortem magnetic resonance imaging to guide the pathologic cut: individualized, 3-dimensionally printed cutting boxes for fixed brains.</a> J Neuropathol Exp Neurol. 73 (8), 780-788 (2014).</li><li>Gait&#225;n, M. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Perivenular+brain+lesions+in+a+primate+multiple+sclerosis+model+at+7-tesla+magnetic+resonance+imaging.">Perivenular brain lesions in a primate multiple sclerosis model at 7-tesla magnetic resonance imaging.</a> Mult Scler. 20 (1), 64-71 (2014).</li></ol>

The authors declare that they have no competing financial interests.

The protocol outlined here enables an accurate comparison between MRI and histology sections. The protocol is presented in a unified format that can be applied to brains of humans or small animals, such as marmosets or rodents. Differences specific to large (human) and small (nonhuman primate and rodent) brains are highlighted, and in the accompanying video and figures we demonstrate the application in the marmoset. Although the approach is straightforward, the method requires many steps as well as the use of several types of software. Moreover, several issues potentially affecting the accuracy of this method are important to mention.
The image quality of the in vivo MRI is an important factor. To minimize the disparity in image resolution between MRI and digitalized histology images, the smallest possible MRI voxel size should be used. This concept also applies to the image quality of the postmortem MRI. While the increased acquisition time in postmortem MRI allows much higher image resolution, the preparation can introduce image artifacts such as focal signal dropouts related to air bubbles. These artifacts can obscure areas of the tissue as well as affect its contour. Moreover, the dimensions of the tissue on the postmortem MRI are likely to be affected by the fixation process and duration. While the in vivo to ex vivo MRI match can be closely approximated by utilizing anatomical landmarks in slice geometry setup during acquisition, a non-linear registration would still be necessary to reach a higher degree of accuracy in matching those two MRI images.
The design of the brain holder and slicer is also a crucial step. In creating the digital model of the brain, a smoothing algorithm is applied that slightly enlarges the model relative to the fixed brain. This enables easy insertion of the brain into its holder and slicer and reduces sharp edges in the holder&#39;s contour. However, if the model is too large (e.g., by more than 5%), the brain might move during the postmortem MRI and/or the sectioning. Another important point is to adapt the design of the brain model so that the cerebellum is properly placed inside the 3D printed object. This can be particularly challenging when the cerebellum has been damaged during the brain extraction at autopsy.
When printing the brain slicer and holder, the type of 3D printer must also be chosen carefully. Some multi-jet printers require post-processing using an oven to remove support material. While these printers can produce objects that are watertight and relatively more durable than desktop fused deposition modeling (FDM) printers, the heating process to remove supports can slightly warp the box, creating blade gaps that are not perfectly perpendicular to the brain contour.
The brain sectioning process is another crucial step. Before cutting the whole brain into slabs, it is important to make sure that the brain is sitting tightly inside the brain slicer: there should be no motion when slight pressure is applied onto the brain. This will make it possible for the blades to cut through the brain at the precise location set by the investigators. A continuous, balanced pressure should be applied to both blade holders when cutting. Depending on the sharpness of the blades and the rigidity of the tissue, a slight transverse cutting motion could be advantageous for maintaining flat cut surfaces.
The paraffin-embedding process can also be a source of misalignment between MRI and histology. If the tissue slab is not sitting flat against the cassette during the embedding process, there will be a tilt between the cutting plane of the microtome and the surface place of the slab. This will require cutting unusable sections to find a flat plane in which all the tissue is exposed. One way to correct for the tilt is by changing the angle of the viewing plane on the high-isotropic-resolution postmortem MRI. However, this is nearly impossible to perform on the in vivo MRI that is usually acquired with anisotropic resolution (typically thick coronal slices).
Finally, the tissue can experience some deformation during the formalin fixation period and paraffin embedding (shrinkage), as well as during the preparation of slides (folding, cracking, wrinkles). Some of these deformations can be corrected by putting the 4-5 &#956;m sections in a water bath before transferring onto slides. Other deformations can be partially solved by performing deformable image coregistration of the histological digitized images to the postmortem MRI images. Nevertheless, minimizing the deformations with careful and skilled practice is the most effective approach to matching MRI volumes to histology sections.
In conclusion, the methodology introduced here enables investigators to accurately assess the underlying pathology of MRI findings. More generally, it is a promising approach for identifying and/or validating novel MRI biomarkers for research studies that target specific pathological processes, such as inflammation or remyelination.

In vivo MRI provides a noninvasive and sensitive measure of tissue integrity at the macroscopic level. Changes in MRI signal intensity seen in vivo are outcome measures in many ongoing clinical trials.1 While the intensity changes seen via MRI can identify areas of abnormality in the context of the whole brain, they are often not sufficiently specific to differentiate pathological processes. This is especially true of dynamic processes involving multiple pathologies. For example, in multiple sclerosis (MS) or its animal model, experimental autoimmune encephalomyelitis (EAE), inflammation, edema, myelin degradation, axonal destruction, gliosis, and neuronal death overlap. 2, 3 To obtain the necessary specificity regarding the underlying pathology, context must be taken into account, together with knowledge of the histology of the MRI-identified abnormal tissues.
However, even in well-controlled animal experiments, matching histology with in vivo MRI is fundamentally challenging for various reasons. First, the difference in dimensional scales between histology sections and MRI is of several orders of magnitude.4 Second, for proper comparison, the orientation of MRI slice plane must match the sectioning plane of the brain tissue when cut. Due to the shape of the brain, it is very difficult to make consistently straight and accurate cuts when the brain is sitting on a flat surface. Third, the large size of the brain relative to a potentially small area of interest (lesion, tumor, etc.) creates a "needle-in-a-haystack" scenario for the pathologist processing the tissue. Fourth, even when the target tissue is found, it is commonly processed in such a way as to render virtually impossible an association with the original MRI data. Finally, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, further complicating the comparison between histology sections and MRI images. 
 Previous attempts to overcome these challenges relied on the use of deformational algorithms to coregister the data and/or placement of fiducial markers within or around the tissue as a reference.5, 6, 7, 8 The former approach requires complex computational models that are particularly susceptible to complications due to data formatting, imaging artifacts, and changes caused by tissue processing.4 On the other hand, the latter approach introduces the possibility of contaminating or otherwise harming the tissue itself.9
The approach described here improves the transition between modalities through the use of postmortem MRI to bridge the gap between in vivo MRI and histology. Postmortem MRI provides three-dimensional (3D) images of the brain at higher resolution than can be achieved in vivo and furthermore provides the data needed for producing a morphologically accurate model of the brain surface. This digital model can then be used to create a 3D-printed custom holder for the brain. With careful positioning, the brain holder allows for precise, MRI-oriented brain sectioning, reducing the need for complex mathematical algorithms, and enables a focus on specific regions for targeted sampling. 
Our laboratory recently introduced new methods for creating custom brain holders and slicers using postmortem MRI and 3D-printing technology for human10 and marmoset brains.4 The two methods allow for a more accurate correlation between MRI and histology in a research setting, and ultimately allow a deeper understanding of the specific pathology underlying MRI abnormalities. Carefully designed experiments, in which the brain is sampled repeatedly over time in vivo, can provide context for interpretation of the pathology, which in turn can add specificity to interpretation of the MRI. Here, we present a modified protocol in a unified framework that can be applied to any brain tissue, whether it derive from nonhuman primates, rodents, or humans. We provide detailed instructions, and a corresponding video, for the marmoset sectioning. Although the overall protocol applies to any type of brain, due to differences in MRI acquisition and tissue size, as well as the challenges encountered when dealing with specific brain types, there are some differences in the approach depending on the type of brain being processed. In this presentation, sections with "human" will denote differences in protocol specific to the human brain.

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utilizing 3d printing technology to merge mri with histology: a protocol for brain sectioning

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume three-dimensionally. While MRI is an extremely sensitive tool for detecting tissue abnormalities, association of signal changes with an underlying pathological process is usually not straightforward. In the central nervous system, for example, inflammation, demyelination, axonal damage, gliosis, and neuronal death may all induce similar findings on MRI. As such, interpretation of MRI scans depends on the context, and radiological-histopathological correlation is therefore of the utmost importance. Unfortunately, traditional pathological sectioning of brain tissue is often imprecise and inconsistent, thus complicating the comparison between histology sections and MRI. This article presents novel methodology for accurately sectioning primate brain tissues and thus allowing precise matching between histology and MRI. The detailed protocol described in this article will assist investigators in applying this method, which relies on the creation of 3D printed brain slicers. Slightly modified, it can be easily implemented for brains of other species, including humans.

The workflow of this method is summarized in Figure 1. Once the brain is sliced, a visual comparison between the MR images and pictures of the superficial surfaces of the slabs shows a good orientation match across multiple slabs (Figure 2). After the slabs are embedded in paraffin, they are sectioned on a microtome and stained. A more thorough comparison between the high resolution postmortem MRI and the stained histology sections demonstrates an accurate and consistent match across all the structures of the marmoset brain (Figure 3).
In this animal model of MS, the animals develop white matter lesions spread throughout the cerebral white matter. These lesions can be detected noninvasively by performing MRI. Figure 4 demonstrates the ability of this technique to elucidate the pathological substrate of the MRI findings. Small lesions detected on in vivo MRI can be tracked on both postmortem MRI and histology. As shown in the insets, demyelination within the lesions is one of the main components driving the MR signal change (hyperintensity compared to surrounding tissue). The histology and postmortem MRI can also show lesions missed on in vivo MRI (Figure 4).
<img alt="Figure 1" src="/files/ftp_upload/54780/54780fig1.jpg" /> 
Figure 1. Workflow for creating a marmoset brain slicer box. The brain is fixed with formalin (A1) and a T2-weighted MRI is acquired with isotropic voxels of 150 &#181;m per edge (A2). Images are processed and thresholded to create a binary mask (A3). The surface is then rendered in 3D modeling software (A4). A Boolean subtraction between a slicer template and the brain model creates a digital model of the brain slicer (B1). The brain slicer box is printed on a 3D printer (B2). The brain is then placed firmly in the slicer box for cutting (B3). <a href="http://cloudflare.jove.com/files/ftp_upload/54780/54780fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54780/54780fig2.jpg" /> 
Figure 2. From left to right: In vivo MRI, postmortem MRI, and tissue slab photograph. Slicing planes were established based on the postmortem MRI (B) and visually compared to the corresponding in vivo MRI slice (A). The brain was then cut, and the resulting slabs were found to be consistent (C). <a href="http://cloudflare.jove.com/files/ftp_upload/54780/54780fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54780/54780fig3.jpg" /> 
Figure 3. High-resolution postmortem MRI and histology section matching. Slabs were embedded in paraffin, cut with a microtome into 4 &#181;m sections, and stained with fast blue and cresyl violet (B). The sections were then visually matched with the 100 &#181;m T2*-weighted MRI based on brain structures (A). Details for acquiring this image are in the supplementary section of the protocol and Table 1. Brain structures: (1) red arrow = internal capsule, blue arrow = anterior commissure; (2) red arrow = putamen, blue arrow = optic tract; (3) red arrow = caudate, blue arrow = hippocampus; (4) red arrow = corpus callosum, blue arrow = cerebral aqueduct; (5) red arrow = inferior colliculus, blue arrow = pyramidal tract. The dashed box in B1 indicates a slice where, either during brain cutting or paraffin embedding, an error caused a slight rotation about the Y axis, leading to mismatch of the anterior commissure on the left. <a href="http://cloudflare.jove.com/files/ftp_upload/54780/54780fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54780/54780fig4.jpg" /> 
Figure 4. Tracking lesions from in vivo MRI to histology section. The in vivo MRI showed no convincing evidence of abnormal hyperintensity signal to suggest lesions in either optic tract (A1). However, the high resolution postmortem MRI shows clear hyper intense lines in both optic tracts (A2). The fast blue/cresyl violet stain of a 4 &#181;m histology section shows that the hyperintense areas seen on the ex vivo MRI are demyelinated (A3). In the cerebral white matter, the in vivo MRI shows subtle hyperintensity bilaterally (B1, enlarged in the insets). The hyperintense areas are more obvious on the high resolution postmortem MRI (B2). The LFB stain of a 4 &#181;m histology section shows that these areas are demyelinated (B3). After comparison with the baseline in vivo MRI and a hemotoxylin-and-eosin stain, the right side was determined to be an anatomical abnormality, not a demyelinated lesion. <a href="http://cloudflare.jove.com/files/ftp_upload/54780/54780fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Supplemental code files" src="/files/ftp_upload/54780/54780supplementalfiles.jpg" /> 
Supplemental code files. Brain_Slicer_Parts_Marmoset.stl: <a href="https://www.jove.com/files/ftp_upload/54780/Brain_Slicer_Parts_Marmoset.stl" target="_blank">Please click here to download this file.</a> Brain_Slicer_Parts_Human.stl: <a href="https://www.jove.com/files/ftp_upload/54780/Brain_Slicer_Parts_Human.stl" target="_blank">Please click here to download this file.</a> Cap_Insert.stl: <a href="https://www.jove.com/files/ftp_upload/54780/Cap_Insert.stl" target="_blank">Please click here to download this file.</a>

Watch this Scientific Journal Video about Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning at JoVE.com

Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning

The overall goal of this protocol is to accurately align magnetic resonance imaging (MRI) image volumes with histology sections via the creation of customized 3D-printed brain holders and slicer boxes.

Magnetic resonance imaging (MRI) allows for the delineation between normal and abnormal tissue on a macroscopic scale, sampling an entire tissue volume ...

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