Department of Radiology, Stanford University, Stanford, CA, 94035, USA.
Department of Bioengineering, Stanford University, Stanford, CA, 94035, USA.
Nat Commun. 2019 Dec 3;10(1):5504. doi: 10.1038/s41467-019-13374-0.
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.
3D 组织学、基于切片的连接图谱和弥散磁共振成像（diffusion MRI）是用于绘制大脑连接的常用技术。虽然有许多特定于模态的工具可用于处理这些数据，但缺乏模态之间的集成。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，使我们能够分析多个纤维束和网络中的组织学特征，并将其与体内生物标志物相关联。我们在小鼠中风模型中应用了我们的管道，不仅证明了 MRI 异常与 CLARITY 组织染色之间存在很强的对应关系，还揭示了与缺血核心相连区域的急性细胞效应。我们通过量化 CLARITY 病毒注射的投射末端来提供改进的连接图，并将弥散 MRI 与 CLARITY 病毒示踪相结合，以跨尺度比较连接图。最后，我们通过这种多模态整合展示了中风的束状组织学变化。该资源可以推动对神经疾病相关网络改变的研究。
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