Overview

Introduction and Features

SpheroidPy is a Python package designed for the management and analysis of in-vitro spheroid data. It offers a framework to facilitate the handling, segmentation, and analysis of extensive collections of spheroid microscopy images. Furthermore, it enables users to extract spatial and temporal features gaining insights into the dynamics of underlying biological processes. While primarily developed and optimized for cancer spheroid proliferation and cytotoxicity assays, it can be adapted to other cell entities and three-dimensional assay systems.

Applications  

The following section will introduce a few of the most important use cases of SpheroidPy and ways it can be incorporated in experimental workflows, improve data processing and yield novel insights.

Proliferation Assays  

Proliferation assays are essential for studying growth kinetics in three-dimensional spheroid cultures. Besides simple growth curves, more complex behaviors - such as the emergence of a necrotic core at a critical size $R_c$ or saturation at large sizes - can be assessed from such data. SpheroidPy facilitates data import, spheroid segmentation, and comprehensive analysis of growth dynamics, including automated statistical evaluations, hence, allowing for an easy-to-streamline workflow from raw data to quantitative insights.

Cytotoxity Assays  

More information on the usage of SpheroidPy for drug testing and cytotoxicity assays will follow soon.
Coming Soon