A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Abstract

AbstractMagnetic resonance imaging (MRI) is the standard tool to image the human brainin vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we presentNextBrain, a next - generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ∼10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to buildthe first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in anyin vivoorex vivobrain MRI scan using theNextBrainatlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolutionex vivoMRI and volumetric analysis of Alzheimer’s disease and healthy brain ageing based on ∼4,000 publicly availablein vivoMRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 μm isotropicex vivohemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge,NextBrainholds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.