4.6 Article

Simultaneous 3D Visualization of the Microvascular and Neural Network in Mouse Spinal Cord Using Synchrotron Radiation Micro-Computed Tomography

期刊

NEUROSCIENCE BULLETIN
卷 37, 期 10, 页码 1469-1480

出版社

SPRINGER
DOI: 10.1007/s12264-021-00715-7

关键词

Sr mu ct; 3D; High-resolution; Neurovascular; Spinal cord

资金

  1. National Natural Science Foundation of China [82030071, 81874004, 81672174]
  2. Key R&D Program of the Hunan Provincial Science & Technology Department [2017SK2061]
  3. Hunan Provincial Department of Finance [(2018)2]
  4. Fundamental Research Funds for the Central Universities of Central South University [2018zzts254]

向作者/读者索取更多资源

Combining Golgi staining with angiography and synchrotron radiation micro-computed tomography (SR mu CT) allowed for the visualization of the 3D neurovascular network in the mouse spinal cord at cellular resolution without destructive sectioning. The 3D morphology of neurons, nerve fiber tracts, and vasculature visualized by SR mu CT was highly consistent with histological methods and could be quantitatively evaluated. This method will be useful in fundamental neuroscience studies.
Effective methods for visualizing neurovascular morphology are essential for understanding the normal spinal cord and the morphological alterations associated with diseases. However, ideal techniques for simultaneously imaging neurovascular structure in a broad region of a specimen are still lacking. In this study, we combined Golgi staining with angiography and synchrotron radiation micro-computed tomography (SR mu CT) to visualize the 3D neurovascular network in the mouse spinal cord. Using our method, the 3D neurons, nerve fibers, and vasculature in a broad region could be visualized in the same image at cellular resolution without destructive sectioning. Besides, we found that the 3D morphology of neurons, nerve fiber tracts, and vasculature visualized by SR mu CT were highly consistent with that visualized using the histological method. Moreover, the 3D neurovascular structure could be quantitatively evaluated by the combined methodology. The method shown here will be useful in fundamental neuroscience studies.

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