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Free Form Deformation-Based Image Registration Improves Accuracy of Traction Force Microscopy
Alvaro Jorge-Peñas1, Alicia Izquierdo-Alvarez1, Rocio Aguilar-Cuenca2
1Biomechanics Section, Department of Mechanical Engineering, KU Leuven, 3001, Leuven, Belgium.
Plos One
|December 8, 2015
Summary
This study introduces a B-spline Free Form Deformation (FFD) algorithm to improve cellular traction force microscopy (TFM). The FFD method accurately quantifies substrate deformation, enhancing traction recovery compared to traditional Particle Image Velocimetry (PIV).
Area of Science:
- Biophysics
- Cell Biology
- Image Analysis
Background:
- Traction Force Microscopy (TFM) measures cellular forces by analyzing substrate deformation.
- Particle Image Velocimetry (PIV) is a common but limited method for quantifying deformations, often underestimating them, especially near cell adhesions.
Purpose of the Study:
- To develop a more accurate method for calculating substrate deformation in TFM.
- To overcome the underestimation of deformations by PIV using a novel image registration approach.
Main Methods:
- Formulated substrate deformation calculation as a non-rigid image registration process.
- Employed a B-spline-based Free Form Deformation (FFD) algorithm using a connected deformable mesh.
- Validated the FFD approach using 3D synthetic and experimental data from endothelial cells on polyacrylamide substrates.
Main Results:
- The FFD algorithm accurately models a wide range of flexible deformations caused by cellular tractions.
- FFD outperforms PIV in quantifying substrate deformation.
- The FFD-derived deformation field leads to a better recovery of traction magnitude and orientation.
Conclusions:
- The B-spline FFD algorithm significantly improves the accuracy of cellular traction recovery in TFM.
- FFD offers a valuable advancement over PIV for analyzing cell-substrate interactions.
