Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI
Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI
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DOI：
10.1038/s41467-019-13374-0
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发表时间：
2019-12-03
影响因子：
16.6
通讯作者：
Zeineh, Michael
中科院分区：
文献类型：
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作者：
Goubran, Maged;Leuze, Christoph;Zeineh, Michael
3D组织学、基于切片的连接图谱和扩散MRI是绘制大脑布线的常用技术。虽然有许多特定模式的工具来处理这些数据，但缺乏跨模式的整合。我们开发了一种自动化资源，将组织学清除的体积与连接图谱和MRI相结合，从而能够分析多个纤维束和网络的组织学特征及其与体内生物标志物的相关性。我们在小鼠中风模型中应用我们的管道，不仅证明了MRI异常与脑组织染色之间的强烈对应关系，而且还揭示了与缺血核心相关的区域中的急性细胞效应。我们提供了改进的地图的连接，量化投影终端从HIVITY病毒注射，并整合扩散MRI与HIVITY病毒跟踪比较跨尺度的连接地图。最后，我们通过这种多模式整合展示了脑卒中的脑道水平组织学变化。这一资源可以推动对神经系统疾病相关网络改变的研究。
3D histology, slice-based connectivity atlases, and diffusion MRI are common techniques to map brain wiring. While there are many modality-specific tools to process these data, there is a lack of integration across modalities. We develop an automated resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling the analysis of histological features across multiple fiber tracts and networks, and their correlation with in-vivo biomarkers. We apply our pipeline in a murine stroke model, demonstrating not only strong correspondence between MRI abnormalities and CLARITY-tissue staining, but also uncovering acute cellular effects in areas connected to the ischemic core. We provide improved maps of connectivity by quantifying projection terminals from CLARITY viral injections, and integrate diffusion MRI with CLARITY viral tracing to compare connectivity maps across scales. Finally, we demonstrate tract-level histological changes of stroke through this multimodal integration. This resource can propel investigations of network alterations underlying neurological disorders.