Population-scale three-dimensional reconstruction and quantitative profiling of microglia arbors

Murad Megjhani, Nicolas Rey-Villamizar, Amine Merouane, Yanbin Lu, Amit Mukherjee, Kristen Trett, Peter Chong, Carolyn Harris, William Shain, Badrinath Roysam
2015 Computer applications in the biosciences : CABIOS  
Motivation: The arbor morphologies of brain microglia are important indicators of cell activation. This article fills the need for accurate, robust, adaptive and scalable methods for reconstructing 3-D microglial arbors and quantitatively mapping microglia activation states over extended brain tissue regions. Results: Thick rat brain sections (100-300 mm) were multiplex immunolabeled for IBA1 and Hoechst, and imaged by step-and-image confocal microscopy with automated 3-D image mosaicing,
more » ... ing seamless images of extended brain regions (e.g. 5903 Â 9874 Â 229 voxels). An over-complete dictionary-based model was learned for the image-specific local structure of microglial processes. The microglial arbors were reconstructed seamlessly using an automated and scalable algorithm that exploits microglia-specific constraints. This method detected 80.1 and 92.8% more centered arbor points, and 53.5 and 55.5% fewer spurious points than existing vesselness and LoG-based methods, respectively, and the traces were 13.1 and 15.5% more accurate based on the DIADEM metric. The arbor morphologies were quantified using Scorcioni's L-measure. Coifman's harmonic co-clustering revealed four morphologically distinct classes that concord with known microglia activation patterns. This enabled us to map spatial distributions of microglial activation and cell abundances. Availability and implementation: Experimental protocols, sample datasets, scalable open-source multi-threaded software implementation (Cþþ, MATLAB) in the electronic supplement, and website (www.farsight-toolkit.org).
doi:10.1093/bioinformatics/btv109 pmid:25701570 pmcid:PMC4481841 fatcat:i3hgc2pbzveqfj4sp65tr2q2zq