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A 3D multimodal micron-scale human brain atlas bridging single cell data, neuropathology and neuroradiology

连接单细胞数据、神经病理学和神经放射学的 3D 多模态微米级人脑图谱

基本信息

批准号：
10370064
负责人：
PARTHA Pratim MITRA
金额：
$ 527.81万
依托单位：
COLD SPRING HARBOR LABORATORY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-15 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10370064
关键词：
3-Dimensional Adult Algorithms Amygdaloid structure Animal Model Architecture Archives Area Atlases Autopsy BRAIN initiative Brain Brain Stem Brain imaging Brain region Callithrix Cell physiology Cells Censuses Clinical Collection Communities Complement Consent Coupled Cryoultramicrotomy Data Data Analyses Data Set Data Store Databases Deposition Exclusion Criteria Functional Magnetic Resonance Imaging Future Generations Geometry Hippocampus (Brain)Histologic Histology Human Hypothalamic structure Image Institution Laboratories Laboratory mice Letters Link Machine Learning Magnetic Resonance Imaging Measurement Medical Medicine Methodology Methods Microscope Microscopic Modality Molecular and Cellular Biology Monkeys Mus Myelin National Institute of Mental Health Neurosciences Process Research Personnel Resolution Resources Scanning Scientist Series Slide Source Stains Structure Techniques Thalamic structure Thick Tissue Banks Tissue Preservation Tissues Training United States National Institutes of Health Ursidae Family Wit annotation system base brain cell brain tissue clinically significant crosslink data centers data portal data repository data sharing digital epigenomics experience genome annotation histological image human data image archival system in vivo machine learning algorithm machine learning method multimodality neuroimaging neuropathology petabyte reference genome success tool transcriptome transcriptomics virtual water diffusion whole slide imaging

项目摘要

Digitized reference brains, also referred to as Common Coordinate Frameworks (CCFs), together with superposed atlas annotations, are of central importance to neuroscience. They bear the same relation to neuroscience as do reference genomes and genome annotations to cellular and molecular biology. Strikingly, however, such reference brains for humans lag far behind the corresponding CCFs for non-human model organisms such as the laboratory mouse. Existing data sets either have sections spaced relatively far apart or lack in-plane resolution down to the micron scale. Crucially, existing data sets are not well connected to the major areas in medicine that deal with the human brain, namely neuroradiology and neuropathology. We will meet this need by creating an unprecedented micron-scale, 3D atlas that combines multiple MRI modalities as well as continuous serial section histology. In particular, the reference atlas will consist of Nissl, Myelin and H&E stains, with 20 micron contiguous serial sections, and approximately ~8000 sections/brain. We will do so using the tape-transfer method, which preserves tissue geometry even in the presence of disconnected pieces to the brain being sectioned, and permits 3D reassembly of the sections into a 3D volume. We will utilize diffeomorphic mapping methods to co-register the MRI and histological data, and will create a human brain CCF in which single-cell transcriptomic and epigenomic data can be pinned in order to create a Human Brain Cell atlas. We will use machine learning approaches to segment cells and processes in these images and to algorithmically detect cytoarchitectonic boundaries; such machine learning methods will also be used to predict histology and cytoarchitecture from MRI data, with our collected data as a training set. We will make our data freely available to scientists as well as medical professionals through an online data portal with a multi-resolution viewer for zooming and panning through terapixel image data, and also deposit the data in a shared data repository to make it easily accessible to other researchers. We will connect our data to a unique on-line neuropathology resource containing over a petabyte of neuropathological images, including H&E stained sections from the coronal plane. We expect that the reference brain data we produce will become the de- facto standard for a high-resolution reference atlas for the human brain.

数字化参考大脑，也被称为公共坐标框架（ccf）