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A Method for 2-Photon Imaging of Blood Flow in the Neocortex through a Cranial Window
Published on: February 25, 2008
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Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method
Jia Meng1, Lingxi Zhou1, Shuhao Qian1
1Zhejiang University, College of Optical Science and Engineering, International Research Center for Advanced Photonics, State Key Laboratory of Modern Optical Instrumentation, Hangzhou, China, China.
Journal of Biomedical Optics
|October 23, 2022
Summary
We developed a new system for deep brain imaging using aggregation-induced emission luminogens (AIEgens) and a novel window optimizing (WO) algorithm. This enables accurate characterization of mouse cerebrovasculature orientation for neuroscience and clinical applications.
Area of Science:
- Neuroscience
- Biomedical Imaging
- Optical Microscopy
Background:
- Deep-imaging of cerebral vessels is crucial for understanding brain structure-function relationships.
- Accurate characterization of cerebrovasculature organization is essential for neurological research.
Purpose of the Study:
- To achieve large-depth imaging of mouse brain vessels using aggregation-induced emission luminogens (AIEgens).
- To develop a novel algorithm for accurate adaptive spatial orientation characterization of cerebral vessels.
Main Methods:
- Utilized AIEgens with near-infrared-II excitation for three-photon fluorescence (3PF) imaging of cerebral blood vessels.
- Developed a window optimizing (WO) method for automated 2D/3D orientation determination.
- Applied the system to map the orientational architecture of mouse cerebrovasculature at millimeter-level depth.
Main Results:
- The WO method demonstrated significantly higher accuracy in 2D and 3D orientation determination compared to fixed-window methods.
- Acquired depth- and diameter-dependent orientation information in vivo with a penetration depth of 800 μm.
- Established the orientational architecture of mouse cerebrovasculature using 3PF imaging and WO analysis.
Conclusions:
- Developed an advanced imaging and analysis system for cerebrovasculature.
- The system facilitates applications in neuroscience and clinical fields.
- Provides a foundation for further research into brain vascular networks.
