Automated 3D Axonal Morphometry of White Matter.
Ali AbdollahzadehIlya BelevichEija JokitaloJussi TohkaAlejandra SierraPublished in: Scientific reports (2019)
Axonal structure underlies white matter functionality and plays a major role in brain connectivity. The current literature on the axonal structure is based on the analysis of two-dimensional (2D) cross-sections, which, as we demonstrate, is precarious. To be able to quantify three-dimensional (3D) axonal morphology, we developed a novel pipeline, called ACSON (AutomatiC 3D Segmentation and morphometry Of axoNs), for automated 3D segmentation and morphometric analysis of the white matter ultrastructure. The automated pipeline eliminates the need for time-consuming manual segmentation of 3D datasets. ACSON segments myelin, myelinated and unmyelinated axons, mitochondria, cells and vacuoles, and analyzes the morphology of myelinated axons. We applied the pipeline to serial block-face scanning electron microscopy images of the corpus callosum of sham-operated (n = 2) and brain injured (n = 3) rats 5 months after the injury. The 3D morphometry showed that cross-sections of myelinated axons were elliptic rather than circular, and their diameter varied substantially along their longitudinal axis. It also showed a significant reduction in the myelinated axon diameter of the ipsilateral corpus callosum of rats 5 months after brain injury, indicating ongoing axonal alterations even at this chronic time-point.
Keyphrases
- white matter
- deep learning
- optic nerve
- electron microscopy
- brain injury
- spinal cord injury
- convolutional neural network
- multiple sclerosis
- machine learning
- optical coherence tomography
- subarachnoid hemorrhage
- high throughput
- induced apoptosis
- systematic review
- cerebral ischemia
- cell proliferation
- clinical trial
- cell cycle arrest
- mass spectrometry
- signaling pathway
- drug induced
- rna seq