Literature DB >> 26051555

AngleJ: A new tool for the automated measurement of neurite growth orientation in tissue sections.

Manuel Ingo Günther1, Martin Günther2, Matthias Schneiders1, Rüdiger Rupp1, Armin Blesch3.   

Abstract

BACKGROUND: Regeneration of axons is one means to restore function after central nervous system and peripheral nervous system injury. Besides increasing the number of regenerating axons, guidance of axons over long distances into and across a lesion site are important determinants for efficient functional restoration. Quantification of axon growth directions is therefore an important measure for the efficacy of neuroregenerative approaches. While several methods exist to manually or automatically trace neurites in images of neuronal cultures to determine their length, tools to automatically measure the effect of neurite guidance in tissue sections do not exist. NEW
METHOD: Because manual measurements of the orientation of regenerating axons are labor-intensive, time-consuming and unreliable, a plugin called AngleJ for the open source software ImageJ was developed that automatically determines axonal orientation in images of immunohistochemically labeled sections of the spinal cord.
RESULTS: Given user-defined filters and thresholds, the plugin accurately detects neurites in sections of the intact spinal cord white matter and a spinal cord hemisection lesion model and measures the distribution pattern of axonal angles. COMPARISON WITH EXISTING
METHODS: Values of automatically measured angles strongly correlate with angles obtained by manual measurements in ImageJ (Pearson correlation 0.88-0.97 for white matter and 0.76-0.94 for axons sprouting into a lesion site).
CONCLUSIONS: AngleJ can be used as a fast alternative to manual angle measurement in conjunction with ImageJ and its source code is freely available to the community.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Angle measurement; Axon growth; Axon guidance; Image analysis; ImageJ; Neurite detection; Regeneration

Mesh:

Substances:

Year:  2015        PMID: 26051555     DOI: 10.1016/j.jneumeth.2015.05.021

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


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