CONICET | Buscador de Institutos y Recursos Humanos

Understanding cellular processes such astumor progression and asymmetric division requires biological models thatreplicate as close as possible the conditions found in living tissue.Tridimensional (3D) cell culture technologies such as spheroids and organoidsprovide this model systems but create new methodological challenges toefficiently characterize their growth and internal structure. In this work, wepresent a modular, extendable and easy to use open source Python toolbox toobtain parameters of interest in this kind of culture. Using glioblastomamulticellular spheroids in suspension and embedded in agarose, we demonstrate apipeline of automatic segmentation of transmission or fluorescence images,recognition of cells clusters, and morphological characterization with thepossibility to apply it to tridimensional reconstructions. By making thisavailable to the scientific community, we expect that improving thecharacterization of 3D cell systems provides a way to better optimize andstandardize culture and assess the effect of drug in screening assays.