Análise quantitativa de culturas de neurônios em matrizes de microeletrodos por meio do processamento de imagens de microscopia confocal de fluorescência

• Ano de defesa: 2015
• Autor(a) principal: Mari, João Fernando
• Orientador(a): Saito, José Hiroki
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• País: BR
• Palavras-chave em Português: Processamento de imagens; Microeletrodos; Microscopia confocal; Neurônios; Segmentação de imagem; Análise quantitativa
• Palavras-chave em Inglês: Microelectrode arrays; Confocal fluorescence microscopy; Cultured DRG neurons; Segmentation; 3D visualization; Quantitative analysis
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/297

Microelectrode arrays (MEA) are devices that allow chemical and electrical stimulation and recording of the extracellular electrical activity from entire neuronal cultures over long periods of time, such as several weeks. Some MEA models have transparent substrate, which enables the imaging of culture using optical microscopy. The images are taken from two channels: fluorescence light and transmitted light channels. In the first one, it is possible to visualize the neurons, while in the other one, it is possible to observe the microelectrodes. The objective of this work is to develop methods that enable performing quantitative analysis of the dissociated culture of rat dorsal root ganglion (DRG) neurons plated on MEA by means of the processing of the images, obtained from confocal fluorescence microscopy. We proposed and developed the following methods in order to achieve this objective: (A) A method to automatically identify the microelectrodes in the transmitted light channel using circular Hough Transform and error correction based on the Delaunay triangulation; (B) the registration of a number of images taken at different parts of the MEA in order to generate a unique and high-resolution representation of the whole culture; (C) the segmentation of the neuron in 2D images taken from the fluorescence channel, composed by the steps: preprocessing, thresholding, morphological filtering, neurons occlusion correction, watershed transform and object classification; (D) 2D quantitative analysis based on the identified microelectrodes and on the segmented neurons; (E) a method for generating 3D polygonal models of the neurons from the volumetric images, to be used for visualizing the culture on the MEA by different points of view and zoom levels; and (F) 3D quantitative analysis performed by the processing of the polygonal surfaces in conjunction with the information about the microelectrodes positioning. The results show that the methods are capable to identify the neurons and microelectrodes on the 2D images efficiently. In the 3D images, the preprocessing step which uses information from the 2D segmentation method, showed to be capable to generate correct polygonal models efficiently. Most of the studies involving the analysis of neuron cultures on MEAs consider only qualitative analysis or simple quantitative measures. However, the methods proposed in this thesis enables to obtain important measures related to the neuron culture, such as: the density and morphology of the neurons, and the spatial and topological distribution of the neurons and microelectrodes. The information about neuron morphology is important because they are related to the behavior of this kind of neuron. The spatial and topological distribution of neurons and microelectrodes are used for providing models of the interface between these elements, for supporting the analysis of the electrophysiological signal recorded by the microelectrodes, as well as in the computational simulations of the neuron culture behavior.