Characterizing the microvasculature of the human brain is critical to advance understanding of brain vascular function. Most methods rely on tissue staining and microscopy in two-dimensions, which pose several challenges to visualize the three-dimensional structure of microvessels. In this study, we used an edge-based segmentation method to extract the 3D vasculature from synchrotron radiation phase-contrast microtomography (PC-mu CT) of two unstained, paraffin-embedded midbrain region of the human brain stem. Vascular structures identified in PC-mu CT were validated with histology of the same specimen. Using the Deriche-Canny edge detector that was sensitive to the boundary between tissue and vascular space, we could segment the vessels independent of signal variations in PC-mu CT images. From the segmented volumetric vasculature, we calculated vessel diameter, vessel length and volume fraction of the vasculature in the superior colliculi. From high resolution images, we found the most frequent vessel diameter to be between 8.6-10.2 mu m. Our findings are consistent with the known anatomy showing two types of vessels with distinctive morphology: peripheral collicular vessels and central collicular vessels. The proposed method opens up new possibilities for vascular research of the central nervous system using synchrotron radiation PC-mu CT of unstained human tissue.
Microvascular imaging of the unstained human superior colliculus using synchrotron-radiation phase-contrast microtomography
Longo, Renata;
2022-01-01
Abstract
Characterizing the microvasculature of the human brain is critical to advance understanding of brain vascular function. Most methods rely on tissue staining and microscopy in two-dimensions, which pose several challenges to visualize the three-dimensional structure of microvessels. In this study, we used an edge-based segmentation method to extract the 3D vasculature from synchrotron radiation phase-contrast microtomography (PC-mu CT) of two unstained, paraffin-embedded midbrain region of the human brain stem. Vascular structures identified in PC-mu CT were validated with histology of the same specimen. Using the Deriche-Canny edge detector that was sensitive to the boundary between tissue and vascular space, we could segment the vessels independent of signal variations in PC-mu CT images. From the segmented volumetric vasculature, we calculated vessel diameter, vessel length and volume fraction of the vasculature in the superior colliculi. From high resolution images, we found the most frequent vessel diameter to be between 8.6-10.2 mu m. Our findings are consistent with the known anatomy showing two types of vessels with distinctive morphology: peripheral collicular vessels and central collicular vessels. The proposed method opens up new possibilities for vascular research of the central nervous system using synchrotron radiation PC-mu CT of unstained human tissue.File | Dimensione | Formato | |
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