RT Journal Article SR Electronic T1 Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography JF eneuro JO eNeuro FD Society for Neuroscience SP ENEURO.0195-17.2017 DO 10.1523/ENEURO.0195-17.2017 A1 Eva L. Dyer A1 William Gray Roncal A1 Judy A. Prasad A1 Hugo L. Fernandes A1 Doga Gürsoy A1 Vincent De Andrade A1 Kamel Fezzaa A1 Xianghui Xiao A1 Joshua T. Vogelstein A1 Chris Jacobsen A1 Konrad P. Körding A1 Narayanan Kasthuri YR 2017 UL http://www.eneuro.org/content/early/2017/09/25/ENEURO.0195-17.2017.abstract AB Methods for resolving the three-dimensional microstructure of the brain typically start by thinly slicing and staining the brain, followed by the imaging of numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography (μCT) for producing mesoscale (approximately 1μm 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for μCT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts.Significance Statement Reconstructing neuroanatomical samples in three dimensions (3D) is challenging, as traditional methods require fine sectioning of tissue and alignment of these sections into a 3D volume. In this manuscript, we present a pipeline for quantifying neuroanatomy with synchrotron X-ray microtomography (μCT), a method that achieves micron resolution over thick millimeter-scale intact samples. As brain tissue can be imaged with μCT without damaging the integrity of the sample, electron microscopy was applied to survey higher-resolution structures. We introduce this data analysis pipeline for blood vessel segmentation and cell detection, as well as producing estimates of cell densities and spatial relationships among cells and blood vessels. These methods promise efficient imaging, reconstruction, and analysis of brain structures using μCT.