Inferring cellular forces from image stacks

Jim H. Veldhuis, Ahmad Ehsandar, Jean Léon Maître, Takashi Hiiragi, Simon Cox, G. Wayne Brodland*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (SciVal)
329 Downloads (Pure)


Although the importance of cellular forces to a wide range of embryogenesis and disease processes is widely recognized, measuring these forces is challenging, especially in three dimensions. Here, we introduce CellFIT-3D, a force inference technique that allows tension maps for three-dimensional cellular systems to be estimated from image stacks. Like its predecessors, video force microscopy and CellFIT, this cell mechanics technique assumes boundary-specific interfacial tensions to be the primary drivers, and it constructs force-balance equations based on triple junction (TJ) dihedral angles. The technique involves image processing, segmenting of cells, grouping of cell outlines, calculation of dihedral planes, averaging along three-dimensional TJs, and matrix equation assembly and solution. The equations tend to be strongly overdetermined, allowing indistinct TJs to be ignored and solution error estimates to be determined. Application to clean and noisy synthetic data generated using Surface Evolver gave tension errors of 1.6–7%, and analyses of eight-cell murine embryos gave estimated errors smaller than the 10% uncertainty of companion aspiration experiments. Other possible areas of application include morphogenesis, cancer metastasis and tissue engineering.

Original languageEnglish
Article number20160261
JournalPhilosophical Transactions B: Biological Sciences
Issue number1720
Publication statusPublished - 19 May 2017


  • Cell mechanics
  • CellFIT
  • CellFIT-3D
  • Force inference
  • Interfacial tensions
  • Video force microscopy (VFM)


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