Understanding the biological implications of cellular mechanotransduction, especially in the context of pathogenesis, requires the accurate resolution of material deformation and strain fields surrounding the cells. This is particularly challenging for cells displaying branched, 3D architectures. Here, we provide a modular approach for 3D image segmentation and strain mapping of topologically complex structures. We describe how to use our approach, using neural cells and networks as an example. In addition to describing how to implement the computational analysis, we provide details of a cell culture protocol that can be used to generate neural networks for analysis and experimentation. This protocol allows for transformation of matrix-induced strains, and their full resolution across single cells or networks in three dimensions. The protocol also provides analyses to compute both the locally varying cytoskeletal strains and the average strain experienced by cells. An additional module allows spatial correlation of these strain maps with cytoskeletal features, including neurite disruptions such as neuronal blebs. Image processing and strain mapping take ≥3 h, with the exact time required being dependent on use case, software familiarity, and file size.
