Multiscale imaging of the rat brain using an integrated diceCT and histology workflow

Abstract

Advancements in tissue visualization techniques have spurred signi cant gains in the biomedical sciences by enabling researchers to integrate their datasets across anatomical scales. Of particular import are techniques that enable the interpolation of multiple hierarchical scales in samples taken from the same individuals. This study demonstrates that two-dimensional histology techniques can be employed on neural tissues following three-dimensional diffusible iodine-based contrast-enhanced computed tomography (diceCT) without causing tissue degradation. This represents the rst step toward a multiscale pipeline for brain visualization. We studied brains from adolescent male Sprague-Dawley rats, comparing experimental (diceCT-stained then de-stained) to control (without diceCT) brains to evaluate neural tissues for immunolabeling integrity, compare somata sizes, and distinguish neurons from glial cells within the telencephalon and diencephalon. We hypothesized that if experimental and control samples do not differ signi cantly in quantitative metrics, brain tissues are robust to the chemical, temperature, and radiation environments required for these multiple, successive imaging protocols. Visualizations for experimental brains were rst captured via micro-computed tomography scanning of isolated, iodine-infused specimens. Samples were then cleared of iodine, serially sectioned, and prepared again using immuno uorescent, uorescent, and cresyl violet labeling, followed by imaging with confocal and light microscopy, respectively. Our results show that many neural targets are resilient to diceCT imaging and compatible with downstream histological staining as part of a low-cost, multiscale brain imaging pipeline.

The first full body diffusible iodine‐based contrast‐enhanced computed tomography dataset and teaching materials for a member of the Testudines

“…We recommend that digital diceCT slices, which are lower resolution than histological sections but can be re‐sectioned into any planar orientation, can serve as a complement to traditional histological sections. Together these tools combine gross anatomical views of structures at myriad angles with target‐specific staining that allows for multi‐scale, cell‐to‐whole body imaging (Gignac et al, 2021).…”

Mapping the avian visual tectofugal pathway using 3D reconstruction

“…With respect to birds, diceCT has been deployed to address questions about the feeding apparatus (Genbrugge et al., 2011; Li & Clarke, 2015), cranial musculoskeletal anatomy (Hadden et al., 2022; Jones et al., 2019; Lautenschlager et al., 2013; To et al., 2021), forelimb musculoskeletal anatomy (Bribiesca‐Contreras & Sellers, 2017), vocal organs (Düring et al., 2013), brain ontogeny and function (Gold et al., 2016; Watanabe et al., 2019; Early et al, 2020), and craniofacial pathology (Gignac, Green, et al., 2021). DiceCT has many advantages for anatomical investigations compared to traditional and other 3D techniques, including low cost, ease of access, nondestructiveness, reversibility, and high‐precision visualization of soft tissues (see Gignac et al., 2016, Gignac, Green, et al., 2021, Gignac, O'Brien, et al., 2021; Gignac & Kley, 2018). These attributes provide diceCT an advantage for comparative studies of avian anatomy and neuroanatomy over other, more traditional approaches.…”

“…The 3D chick tectofugal system is based on a multimodal visualization technique that couples histology and diceCT imaging. Each imaging methodology has advantages; however, when coupled, the techniques appear to more than complement one another (e.g., Gignac, O'Brien, et al., 2021). In particular, histological sections offer cell‐specific staining and exceptionally high resolution.…”

“…Although diceCT employs X‐ray‐based computed tomography, the use of contrast agents which bind selectively to the white and gray matter of the brain ensures that neuroanatomical features can be resolved in 3D (Gignac & Kley, 2014, 2018). DiceCT brain data sets show tissue contrast like those of T1‐weighted magnetic resonance imaging (MRI) slices but at resolutions comparable to micro‐MRI (Gignac, O'Brien, et al., 2021). Moreover, diceCT can be integrated with histological data sets to provide orders of magnitude of structural detail, from cellular to brain to organismal levels of organization (Gignac, Green, et al., 2021; Gignac, O'Brien, et al., 2021).…”

“…DiceCT brain data sets show tissue contrast like those of T1‐weighted magnetic resonance imaging (MRI) slices but at resolutions comparable to micro‐MRI (Gignac, O'Brien, et al., 2021). Moreover, diceCT can be integrated with histological data sets to provide orders of magnitude of structural detail, from cellular to brain to organismal levels of organization (Gignac, Green, et al., 2021; Gignac, O'Brien, et al., 2021). As a result, we now have the opportunity to develop 3D, highly detailed, and descriptive models of the neural circuitry controlling various aspects of behavior, including the visual behaviors of birds.…”