TY - JOUR T1 - 3DMorph automatic analysis of microglial morphology in 3 dimensions from <em>ex vivo</em> and <em>in vivo</em> imaging JF - eneuro JO - eNeuro DO - 10.1523/ENEURO.0266-18.2018 SP - ENEURO.0266-18.2018 AU - Elisa M. York AU - Jeffrey M. LeDue AU - Louis-Philippe Bernier AU - Brian A. MacVicar Y1 - 2018/11/19 UR - http://www.eneuro.org/content/early/2018/11/19/ENEURO.0266-18.2018.abstract N2 - Microglia are dynamic immune cells of the central nervous system, and their morphology is commonly used as a readout of cellular function. However, current morphological analysis techniques rely on either tracing of cells or 2D projection analysis, which are time-consuming, subject to bias, and may ignore important three-dimensional (3D) information. Therefore, we have created 3DMorph, a Matlab-based script that analyzes microglial morphology from 3D data. The program initially requires input of threshold levels, cell size expectations, and preferred methods of skeletonization. This makes 3DMorph easily scalable and adaptable to different imaging parameters or cell types. After these settings are defined, the program is completely automatic and can batch process files without user input. Output data includes cell volume, territorial volume, branch length, number of endpoints and branch points, and average distance between cells. We show that 3DMorph is accurate when compared to manual tracing, with significantly decreased user input time. Importantly, 3DMorph is capable of processing in vivo microglial morphology, as well as other 3D branching cell types, from mouse cranial windows or acute hippocampal slices. Therefore, we present a novel, user-friendly, scalable, and semi-automatic method of analyzing cell morphology in 3 dimensions. This method should improve the accuracy of cell measurements, remove user bias between conditions, increase reproducibility between experimenters and labs, and reduce user input time. We provide this open source code on GitHub so that it is free and accessible to all investigators.Significance Statement Microglial morphology is often considered to be an indicator of cellular activity, however current techniques to analyze morphology either lose valuable z-dimension information or are time intensive to perform. Therefore, we introduce 3DMorph, a MATLAB-based program that semi-automatically processes individual microglial morphology from overlapping 3D clusters, improving accuracy and processing time compared to current tools. 3DMorph is straightforward to use and adaptable to many imaging or experimental parameters. Once user settings are selected, 3DMorph can run in batch mode to automatically process multiple files. We validate 3DMorph against current techniques, and demonstrate the ability to detect differences in microglial morphologies from different ex vivo experimental conditions, as well as from in vivo data, and images of other branching cell types. ER -