Semi-automated protocol to quantify and characterize fluorescent three-dimensional vascular images

Area of Science:

• * Biomedical imaging
• * Tissue engineering
• * Vascular biology

Background:

• * Microvasculature is crucial for physiological functions and its abnormalities indicate disease.
• * Traditional methods like immunohistochemistry are limited for whole-organ vascular analysis.
• * Three-dimensional (3D) imaging offers a more comprehensive approach to visualize tissue vascular architecture.

Purpose of the Study:

• * To describe a complete protocol for characterizing mouse organ vasculature using 3D imaging.
• * To establish a semi-automated method for quantifying 3D vascular images.
• * To validate the accuracy of automated vascular segmentation against manual segmentation.

Main Methods:

• * Fluorescently labeling blood vessels within organs.
• * Applying optical clearing techniques to render tissues transparent.
• * Acquiring 3D images of the vascular network.
• * Utilizing a semi-automated approach for image quantification and analysis.

Main Results:

• * Developed and validated a comprehensive 3D imaging protocol for whole-organ vasculature.
• * Achieved high accuracy in automated vascular segmentation (83% sensitivity, 91% specificity) compared to manual segmentation.
• * Demonstrated a reliable and timely method for quantifying and characterizing vascular networks.

Conclusions:

• * The described protocol provides a robust method for analyzing microvasculature in whole organs.
• * This approach is adaptable to various tissue clearing techniques and vascular labels.
• * Enables efficient and accurate characterization of vascular networks for research and diagnostics.