A novel workflow for 3D imaging and spatial analysis of nerves in bone

Area of Science:

• Bone biology and neurobiology
• Advanced imaging techniques
• Computational biology

Background:

• Peripheral nerves in bone regulate bone function and response to stimuli.
• Visualizing and segmenting small, filamentous nerves within dense bone tissue is challenging.
• Current manual segmentation methods are subjective, time-consuming, and inadequate for quantification.

Purpose of the Study:

• To develop and validate a novel workflow for 3D imaging and spatial analysis of nerves in bone.
• To improve the accuracy and efficiency of skeletal nerve segmentation.
• To overcome limitations of traditional manual segmentation methods.

Main Methods:

• Utilized lightsheet microscopy (LSM) for high-resolution 3D imaging of nerves in murine calvaria (uninjured and injured).
• Employed Ilastik® open-source software for automated nerve segmentation within bone tissue.
• Validated the workflow across diverse skeletal bone contexts, including varied samples, clearing methods, and inflammatory states.

Main Results:

• Successfully generated accurate 3D segmentations of peripheral nerves in bone using LSM and Ilastik®.
• Significantly reduced reliance on manual segmentation, enhancing efficiency and objectivity.
• Demonstrated broad applicability of the workflow across different skeletal imaging scenarios.

Conclusions:

• The developed workflow provides a robust method for 3D imaging and spatial analysis of bone innervation.
• This approach enables precise characterization of nerve patterning in bone, aiding in the study of bone homeostasis, injury, and disease.
• Offers potential for novel insights into spatially regulated phenomena within the bone microenvironment.