  Lung injuries, such as ventilator-induced lung injury and radiation-induced
lung injury, can lead to heterogeneous alterations in the biomechanical
behavior of the lungs. While imaging methods, e.g., X-ray and static computed
tomography (CT), can point to regional alterations in lung structure between
healthy and diseased tissue, they fall short of delineating timewise kinematic
variations between the former and the latter. Image registration has gained
recent interest as a tool to estimate the displacement experienced by the lungs
during respiration via regional deformation metrics such as volumetric
expansion and distortion. However, successful image registration commonly
relies on a temporal series of image stacks with small displacements in the
lungs across succeeding image stacks, which remains limited in static imaging.
In this study, we have presented a finite element (FE) method to estimate
strains from static images acquired at the end-expiration (EE) and
end-inspiration (EI) timepoints, i.e., images with a large deformation between
the two distant timepoints. Physiologically realistic loads were applied to the
geometry obtained at EE to deform this geometry to match the geometry obtained
at EI. The results indicated that the simulation could minimize the error
between the two geometries. Using four-dimensional (4D) dynamic CT in a rat,
the strain at an isolated transverse plane estimated by our method showed
sufficient agreement with that estimated through non-rigid image registration
that used all the timepoints. Through the proposed method, we can estimate the
lung deformation at any timepoint between EE and EI. The proposed method offers
a tool to estimate timewise regional deformation in the lungs using only static
images acquired at EE and EI.
