NeuronMetrics: Software for semi-automated processing of cultured neuron images

• Published in: Brain research Vol. 1138; pp. 57 - 75
• Main Authors: Narro, Martha L., Yang, Fan, Kraft, Robert, Wenk, Carola, Efrat, Alon, Restifo, Linda L.
• Format: Journal Article
• Language: English
• Published: London Elsevier B.V 23.03.2007; Amsterdam Elsevier; New York, NY
• Subjects: Animals; Automation; Biological and medical sciences; Branch count; Cell-based assay; Cells, Cultured; Central Nervous System - cytology; Central Nervous System - ultrastructure; Convex hull; Diagnostic Imaging; Drosophila; Fasciculation; Fluorescent Dyes; Fundamental and applied biological sciences. Psychology; General aspects. Models. Methods; Microscopy; Mushroom body; Neurite arbor; Neurites - ultrastructure; Neurology; Neurons - ultrastructure; Software - standards; Software development; Time Factors; Vertebrates: nervous system and sense organs; Software development; Drosophila; Mushroom body; HRP; Fasciculation; Neurite arbor; CNS; ROI; βgal; Branch count; Convex hull; PI; Cell-based assay; Polarity Index; central nervous system; β-galactosidase; horseradish peroxidase; region of interest; Neurite; Drosophila Mushroom body Software development Cell-based assay Convex hull Branch count Fasciculation Neurite arbor; Insecta; Corpora pedunculata; In vitro; Semiautomatic; Drosophilidae; Automatic processing; Neuron; Arthropoda; Development; Software; Invertebrata; Diptera
• ISSN: 0006-8993; 1872-6240; 1872-6240
• DOI: 10.1016/j.brainres.2006.10.094

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics™ for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of ∼ 60 2D images is 1.0–2.5 h, from a folder of images to a table of numeric data. NeuronMetrics' output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery.