Three-dimensional Histomorphometry of Wetmounted Peripheral Nerve
Iván Coto Hernández, PhD, Mass Eye and Ear, Boston, MA and Nate Jowett, MD, Facial Nerve Center - Dept. of Otolaryngology, Harvard Medical School / Massachusetts Eye and Ear, Boston, MA
Background: Conventional nerve histomorphometry is typically performed on ultrathin axial sections using bright-field microscopy following lengthy chemical staining and resin sectioning steps. Herein is described a rapid technique for three dimensional histomorphometry of peripheral nerve that obviates need for sectioning.
Method & Materials: Fresh healthy human nerve samples obtained during free tissue transfer procedures were fixed in 2% phosphate-buffered paraformaldehyde, and stained with CellMask™ Plasma Membrane. Wet-mount control- and regenerating nerves were imaging using two-photon microscopy aided by adaptive optics to correct aberration for deep imaging. Machine learning based image analysis software (Aivia v8.8, DRVision Technologies LLC, Bellevue, WA) was used for deep learning deconvolution to enhance the image quality and three-dimensional segmentation for near intraoperative assessment of peripheral nerve myelinated axon count.
Results: Three-dimensional reconstruction of human peripheral nerve was obtained in high-throughput fashion. Automated myelinated axon quantification using machine learning algorithm is demonstrated.
Conclusions: A high-throughput combination of two-photon microscopy and machine learning based image analysis allowing for three dimensional segmentation of peripheral nerve has been described. The potential of this technique to inform intraoperative decision-making through rapid automated quantification of myelinated axons is discussed.
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