Optical coherence tomography (OCT) has shown an affinity for imaging white matter using intrinsic signals. Combined with an automated vibratome and mosaic imaging, serial blockface histology (SBH) can yield whole-brain white matter images at high resolution. A current drawback of SBH is the lack of real-time information that complicates the localization of brain structures during imaging. To address this, imaged slices can be registered to a pre-existing 3D volume to provide more contextual information during the acquisition. 3D brain image registration is a process where a volume is aligned to a standard template to perform further analysis in a common reference frame. Without a full 3D volume, however, this slice-to-volume registration often proves difficult. The search space is large, and the limited information hampers existing algorithms. In this article, we present a neural network that predicts the 3D position of a 2D slice and aligns it to the corresponding slice in 3D template volume. The network uses a VGG16 backbone to extract features, followed by fully connected layers to predict the transformations. Six mouse brains at a resolution of 25μm, imaged using Serial OCT, have been used to train the network. The loss is calculated by taking the Euclidian distance between the predictions and the ground truth, which has been randomly sampled from the volume. Applications for this model are 2D to 3D slice registration, providing contextual information during serial OCT acquisitions such as the progress, or a parcelization of the current slice into its brain regions.
Previous studies have shown that the optical coherence tomography (OCT) signal in white matter (WM) is affected by the WM fiber bundles orientation with respect to the microscope’s optical axis. In this paper, we aim to exploit this contrast mechanism to generate a multi-orientation representation of WM microstructure in whole mouse brains. To achieve this, a serial blockface histology set-up has been developed combined with spectral domain OCT equipped with a long-range 10x magnification objective, achieving a near isotropic resolution of 3 micron laterally (xy) and 3.5 micron axially (z). With this imaging system, a map of WM structures can be generated for an entire agarose embedded mouse brain. To precisely control the mouse brain orientation within the agarose, we designed a multi-part 3D printed mold, which allows us to choose the vibratome’s slicing plane (e.g., coronal, axial, sagittal, etc.). After the serial OCT acquisition, every slice is reconstructed as 2D images and stacked to obtain a 2.5D volume. The reconstruction process uses a nextflow computational pipeline, allowing us to parallelize the calculations. Our proposed imaging method emphasizes different WM structures according to their orientation, which we illustrated in the mouse’s anterior commissure olfactory limb. This structure is very bright when observed in axial slices, whereas it has a darker appearance in the coronal slices. Using this method, we plan to acquire whole mouse brains oriented in multiple directions and to create a multi-orientation mouse brain template, which we believe will prove useful to get a better understanding of complex WM microstructure geometries, such as fiber crossing areas.
The Allen Mouse Brain Connectivity Atlas (AMBCA) offers a high-resolution map of neural connections detailing axonal projections labeled by viral tracers. It is a unique tool for studying structural connectivity and better understanding the white matter pathways of the gene mouse brain. But, the analysis and comparison of these data are limited to a simple visualization on the Allen website and have no direct relationship with specific User data. Here, we propose a series of python-based tools to operate with AMBCA data in the User’s data space. Our method is based on ”back and forth” actions between Allen and User data using the Allen Software Development Kit (AllenSDK) to import data from the Allen Institute and the Python package ANTsPyX for registration. A transformation matrix is calculated with ANTsPyX to overlay, for instance, Allen’s projection density maps with a diffusion MRI-based tractography in the User space. Conversely, applying the inverse transformation to a specific location along a white matter bundle within the User space allows us to recover which experiments were done at this particular location in the Allen Mouse brain Common Coordinate Framework (CCFv3). Thus, both data can be used in a natural interaction, e.g., by inspecting them in a visualization tool such as the MI-Brain software. This series of tools will offer an attractive solution for researchers with neural tracing and/or tractography data to be combined with the AMBCA. The code is available at: https: //github.com/linum-uqam/m2m.
To obtain an accurate representation of a brain structural connectivity, diffusion MRI and fiber tracking depend on a good understanding of white matter fiber structures. Although the tracking methods work well when performed in single orientation fiber bundles, most methods are limited in more complex cases, especially to take into account crossing, fanning, and kissing fibers. A recent international fiber tracking challenge concluded that most tracking algorithms generated 4–5 times more false positive tracks than true tracks on average. This was attributed in large part to a lack of knowledge about the fiber crossing geometry. There is thus a dire need to study more complex fiber geometries to improve the tractography algorithms, for example by classifying those geometries into characteristic crossing topologies (e.g., fanning, curving, bottleneck, pure crossing, ...). Here, we propose a multimodal neuroimaging pipeline to identify and acquire fiber crossing areas in whole mouse brains. Our method uses the Allen Mouse Brain connectivity atlas and tractogram analysis using diffusion MRI techniques to identify candidate regions of interests containing fiber crossings based on two predetermined retrograde viral injection site locations. Based on serial OCT acquisitions, we confirmed the location of crossings. Further experiments will validate in detail the structural nature of crossings using retrograde injections of fluorescent tracers and whole mouse brain serial blockface histology. We believe that this new methodological approach will provide indispensable data for the development of a new generation of tractography algorithms that better resolve complex fiber geometries.
An automated dual-resolution serial optical coherence tomography (2R-SOCT) scanner is developed. The serial histology system combines a low-resolution (25 μm / voxel) 3 × OCT with a high-resolution (1.5 μm / voxel) 40 × OCT to acquire whole mouse brains at low resolution and to target specific regions of interest (ROIs) at high resolution. The 40 × ROIs positions are selected either manually by the microscope operator or using an automated ROI positioning selection algorithm. Additionally, a multimodal and multiresolution registration pipeline is developed in order to align the 2R-SOCT data onto diffusion MRI (dMRI) data acquired in the same ex vivo mouse brains prior to automated histology. Using this imaging system, 3 whole mouse brains are imaged, and 250 high-resolution 40 × three-dimensional ROIs are acquired. The capability of this system to perform multimodal imaging studies is demonstrated by labeling the ROIs using a mouse brain atlas and by categorizing the ROIs based on their associated dMRI measures. This reveals a good correspondence of the tissue microstructure imaged by the high-resolution OCT with various dMRI measures such as fractional anisotropy, number of fiber orientations, apparent fiber density, orientation dispersion, and intracellular volume fraction.
Given known correlations between vascular health and cognitive impairment, the development of tools to image microvasculature in the whole brain could help investigate these correlations. We explore the feasibility of using an automated serial two-photon microscope to image fluorescent gelatin-filled whole rodent brains in three-dimensions (3-D) with the goal of carrying group studies. Vascular density (VD) was computed using automatic segmentation combined with coregistration techniques to build a group-level vascular metric in the whole brain. Focusing on the medial prefrontal cortex, cerebral cortex, the olfactory bulb, and the hippocampal formation, we compared the VD of three age groups (2-, 4.5-, and 8-months-old), for both wild type mice and a transgenic model (APP/PS1) with pathology resembling Alzheimer’s disease (AD). We report a general loss of VD caused by the aging process with a small VD increase in the diseased animals in the somatomotor and somatosensory cortical regions and the olfactory bulb, partly supported by MRI perfusion data. This study supports previous observations that AD transgenic mice show a higher VD in specific regions compared with WT mice during the early and late stages of the disease (4.5 to 8 months), extending results to whole brain mapping.
Aging is accompanied by complex structural changes in the heart. To explore this remodeling, we used a serial optical coherence tomography scanner to image the entire heart at a microscopic resolution. The imaging platform combines optical coherence microscopy to vibratome sectioning to automatically image every subsection of the sample. Post-processing algorithms were then used to stitch back together the sample in a large 3D dataset. We imaged the heart of 7 young (4 months) and 5 old (24 months) wildtype mice (C57B16) with the imaging platform. Optical coherence tomography of the myocardium reveals myofiber orientation that changes linearly from the endocardium to the epicardium. This change in orientation also varies with the distance from the apex of the heart : close to the apex, the change in myofiber orientation with respect to wall depth is larger. In old mice, this change was lower when compared to young mice due to remodelling. As reported in other works, the average volume of old mice hearts (97 ± 3 mm3) was significantly larger (p<0.05) when compared to young hearts (87 ± 3 mm3). Myocardial wall thickening was accompanied by a reduction of light attenuation in the endocardium. Attenuation coefficient in old mice endocardium was measured at 15.4 ± 0.4 cm-1, compared to 18.6 ± 0.5 cm-1 in young mice, which was significantly lower (p<0.05). The use of a serial optical coherence tomography allows new insight into fine changes of the whole heart.
In this study, an automated serial two-photon microscope was used to image a fluorescent gelatin filled rodent’s brain in 3D. A method to compute vascular density using automatic segmentation was combined with coregistration techniques to build group-level vasculature metrics. By studying the medial prefrontal cortex and the hippocampal formation of 3 age groups (2, 4.5 and 8 months old), we compared vascular density for both WT and an Alzheimer model transgenic brain (APP/PS1). We observe a loss of vascular density caused by the ageing process and we propose further analysis to confirm our results.
High resolution imaging of whole rodent brains using serial OCT scanners is a promising method to investigate microstructural changes in tissue related to the evolution of neuropathologies. Although micron to sub-micron sampling resolution can be obtained by using high numerical aperture objectives and dynamic focusing, such an imaging system is not adapted to whole brain imaging. This is due to the large amount of data it generates and the significant computational resources required for reconstructing such volumes. To address this limitation, a dual resolution serial OCT scanner was developed. The optical setup consists in a swept-source OCT made of two sample and reference arms, each arm being coupled with different microscope objectives (3X / 40X). Motorized flip mirrors were used to switch between each OCT arm, thus allowing low and high resolution acquisitions within the same sample. The low resolution OCT volumes acquired with the 3X arm were stitched together, providing a 3D map of the whole mouse brain. This brain can be registered to an OCT brain template to enable neurological structures localization. The high resolution volumes acquired with the 40X arm were also stitched together to create local high resolution 3D maps of the tissue microstructure. The 40X data can be acquired at any arbitrary location in the sample, thus limiting storage-heavy high resolution data to application restricted to specific regions of interest. By providing dual-resolution OCT data, this setup can be used to validate diffusion MRI with tissue microstructure derived metrics measured at any location in ex vivo brains.
An automated serial histology setup combining optical coherence tomography (OCT) imaging with vibratome sectioning was used to image eight wild type mouse brains. The datasets resulted in thousands of volumetric tiles resolved at a voxel size of (4.9×4.9×6.5) μm3 stitched back together to give a three-dimensional map of the brain from which a template OCT brain was obtained. To assess deformation caused by tissue sectioning, reconstruction algorithms, and fixation, OCT datasets were compared to both in vivo and ex vivo magnetic resonance imaging (MRI) imaging. The OCT brain template yielded a highly detailed map of the brain structure, with a high contrast in white matter fiber bundles and was highly resemblant to the in vivo MRI template. Brain labeling using the Allen brain framework showed little variation in regional brain volume among imaging modalities with no statistical differences. The high correspondence between the OCT template brain and its in vivo counterpart demonstrates the potential of whole brain histology to validate in vivo imaging.
An automated massive histology setup combined with an optical coherence tomography (OCT) microscope was used to image a total of n=5 whole mouse brains. Each acquisition generated a dataset of thousands of OCT volumetric tiles at a sampling resolution of 4.9×4.9×6.5 μm. This paper describes techniques for reconstruction and segmentation of the sliced brains. In addition to the measured OCT optical reflectivity, a single scattering photon model was used to compute the attenuation coefficients within each tissue slice. Average mouse brain templates were generated for both the OCT reflectivity and attenuation contrasts and were used with an n-tissue segmentation algorithm. To better understand the brain tissue OCT contrast origin, one of the mouse brains was acquired using dMRI and coregistered to its corresponding assembled brain. Our results indicate that the optical reflectivity in a fiber bundle varies with its orientation, its fiber density, and the number of fiber orientations it contains. The OCT mouse brain template generation and coregistration to dMRI data demonstrate the potential of this massive histology technique to pursue cross-sectional, multimodal, and multisubject investigations of small animal brains.
A whole rodent brain was imaged using an automated massive histology setup and an Optical Coherence Tomography (OCT) microscope. Thousands of OCT volumetric tiles were acquired, each covering a size of about 2.5x2.5x0.8 mm3 with a sampling resolution of 4.9x4.9x6.5 microns. This paper shows the techniques for reconstruction, attenuation compensation and segmentation of the sliced brains. The tile positions within the mosaic were evaluated using a displacement model of the motorized stage and pairwise coregistration. Volume blending was then performed by solving the 3D Laplace equation, and consecutive slices were assembled using the cross-correlation of their 2D image gradient. This reconstruction algorithm resulted in a 3D map of optical reflectivity for the whole brain at micrometric resolution. OCT tissue slices were then used to estimate the local attenuation coefficient based on a single scattering photon model. The attenuation map obtained exhibits a high contrast for all white matter fibres, regardless of their orientation. The tissue optical attenuation from the intrinsic OCT reflectivity contributes to better white matter tissue segmentation. The combined 3D maps of reflectivity and attenuation is a step toward the study of white matter at a microscopic scale for the whole brain in small animals.
A combined serial OCT/confocal scanner was designed to image large sections of biological tissues at microscopic resolution. Serial imaging of organs embedded in agarose blocks is performed by cutting through tissue using a vibratome which sequentially cuts slices in order to reveal new tissue to image, overcoming limited light penetration encountered in microscopy. Two linear stages allow moving the tissue with respect to the microscope objective, acquiring a 2D grid of volumes (1x1x0.3 mm) with OCT and a 2D grid of images (1x1mm) with the confocal arm. This process is repeated automatically, until the entire sample is imaged. Raw data is then post-processed to re-stitch each individual acquisition and obtain a reconstructed volume of the imaged tissue. This design is being used to investigate correlations between white matter and microvasculature changes with aging and with increase in pulse pressure following transaortic constriction in mice. The dual imaging capability of the system allowed to reveal different contrast information: OCT imaging reveals changes in refractive indices giving contrast between white and grey matter in the mouse brain, while transcardial perfusion of FITC or pre-sacrifice injection of Evans Blue shows microsvasculature properties in the brain with confocal imaging.
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