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Automated quantification of neurite outgrowth orientation distributions on patterned surfaces
Matthew Payne1, Dadong Wang, Catriona M Sinclair
1Quantitative Imaging Group, Division of Computational Informatics, CSIRO, North Ryde, NSW 1670, Australia. School of Medicine, University of Western Sydney, Campbelltown, NSW 2560, Australia.
Objective:
We have developed an image analysis methodology for quantifying the anisotropy of neuronal projections on patterned substrates.
Approach:
Our method is based on the fitting of smoothing splines to the digital traces produced using a non-maximum suppression technique. This enables precise estimates of the local tangents uniformly along the neurite length, and leads to unbiased orientation distributions suitable for objectively assessing the anisotropy induced by tailored surfaces.
Main Results:
In our application, we demonstrate that carbon nanotubes arrayed in parallel bundles over gold surfaces induce a considerable neurite anisotropy; a result which is relevant for regenerative medicine.
Significance:
Our pipeline is generally applicable to the study of fibrous materials on 2D surfaces and should also find applications in the study of DNA, microtubules, and other polymeric materials.
