The development of optical clearing methods 9, 10 has allowed mouse organs, including the brain, to be rendered completely transparent, thus overcoming this limitation. The capillary network can be visualized at high resolution via optical microscopy however, depth is limited when acquiring images from opaque samples. Other minimally invasive methodologies allow only poor visualization of smaller superficial vessels, without reaching capillary-level resolution and without including deep regions 5, 6, 7, 8. Although large vessels in the whole mouse brain can be detected non-invasively with a variety of techniques 1, 2, 3, 4, these methods provide a rather coarse resolution. Mapping the fine anatomical details of capillaries over the entire mouse brain has been challenging because it requires micrometre resolution coupled with fast acquisition speeds in order to cover the entire sample volume in a reasonable time period. Despite the fundamental importance of this system, we do not have a complete topological understanding of the capillary network through which the exchange of substances and metabolites takes place. Neuronal activity relies on an intricate network of blood vessels that delivers oxygen and nutrients for neuronal metabolism. We believe our new method will be valuable for future brain-wide investigations of the capillary network. Furthermore, our novel method is compatible with endogenous fluorescence, thus allowing simultaneous investigations of vasculature and genetically targeted neurons. This method significantly improves image contrast, particularly in depth, thereby allowing reliable application of automatic segmentation algorithms, which play an increasingly important role in high-throughput imaging of the terabyte-sized datasets now routinely produced. Here, we demonstrate a novel approach that improves vascular demarcation by combining CLARITY with a vascular staining approach that can fill the entire blood vessel lumen and imaging with light-sheet fluorescence microscopy. However, despite this fundamental role, a detailed reconstruction of the brain-wide vasculature at the capillary level remains elusive, due to insufficient image quality using the best available techniques. All rights reserved.The distinct organization of the brain’s vascular network ensures that it is adequately supplied with oxygen and nutrients. We propose that our automated brain mapping method enables greater efficiency and consistency in mouse neuropathologic assessments.Īutomated image analysis Brain atlas Brain map Image segmentation Mouse histologic sections.Ĭopyright © 2018 Elsevier B.V. Optical density quantification results were comparable to those from time-consuming, manually drawn hippocampal delineations on the IHC-stained sections.Ĭompared to other published methods, our method requires less manual input, and has been validated comprehensively using a secondary atlas, as well as manually annotated brain IHC sections from 68 study mice. Nissl-stained sections were mapped and hippocampal boundaries transferred to adjacent immunohistochemically stained sections. We subsequently applied our method to mouse brain sections from an in vivo study where the hippocampus was the structure of interest. Brain regions mapped from FP Nissl-stained sections and calculated volumes were similar to structure delineations and volumes derived from corresponding FP illustrations. The method's accuracy was first assessed by comparing the mapping results to structure delineations from the Franklin and Paxinos (FP) mouse brain atlas. The method utilizes the publicly available Allen Brain Atlas to map brain regions on digitized Nissl-stained sections. We developed an automated brain mapping method that identifies neuroanatomic structures in mouse histologic coronal brain sections. Automated image analysis is a powerful tool that can radically reduce the workload associated with evaluating brain histologic sections. Histologic evaluation of the central nervous system is often a critical endpoint in in vivo efficacy studies, and is considered the essential component of neurotoxicity assessment in safety studies.
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