TY - JOUR T1 - Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography JF - eneuro JO - eNeuro DO - 10.1523/ENEURO.0195-17.2017 SP - ENEURO.0195-17.2017 AU - Eva L. Dyer AU - William Gray Roncal AU - Judy A. Prasad AU - Hugo L. Fernandes AU - Doga Gürsoy AU - Vincent De Andrade AU - Kamel Fezzaa AU - Xianghui Xiao AU - Joshua T. Vogelstein AU - Chris Jacobsen AU - Konrad P. Körding AU - Narayanan Kasthuri Y1 - 2017/09/25 UR - http://www.eneuro.org/content/early/2017/09/25/ENEURO.0195-17.2017.abstract N2 - 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. ER -