Automatic Segmentation of Mechanically Inhomogeneous Tissues Based on Deformation Gradient Jump

Abstract

Variations in properties, active behavior, injury, scarring, and/or disease can all cause a tissue’s mechanical behavior to be heterogeneous. Advances in imaging technology allow for accurate full-field displacement tracking of both in vitro and in vivo deformation from an applied load. While detailed strain fields provide some insight into tissue behavior, material properties are usually determined by fitting stress-strain behavior with a constitutive equation. However, the determination of the mechanical behavior of heterogeneous soft tissue requires a spatially varying constitutive equation (i.e. one in which the material parameters vary with position). We present an approach that computationally dissects the sample domain into many homogeneous subdomains, wherein subdomain boundaries are formed by applying a betweenness based graphical analysis to the deformation gradient field to identify locations with large discontinuities. This novel partitioning technique successfully determined the shape, size and location of regions with locally similar material properties for: (1) a series of simulated soft tissue samples prescribed with both abrupt and gradual changes in anisotropy strength, prescribed fiber alignment, stiffness, and nonlinearity, (2) tissue analogs (PDMS and collagen gels) which were tested biaxially and speckle tracked (3) and soft tissues which exhibited a natural variation in properties (cadaveric supraspinatus tendon), a pathologic variation in properties (thoracic aorta containing transmural plaque), and active behavior (contracting cardiac sheet). The routine enables the dissection of samples computationally rather than physically, allowing for the study of small tissues specimens with unknown and irregular inhomogeneity.

Marker-Free Tracking of Facet Capsule Motion Using Polarization-Sensitive Optical Coherence Tomography

“…The method shows that surface motion can be tracked by utilizing inherent structural properties of the tissue. This approach could be combined with methods such as those of Boyle et al 6 or Witzenburg et al 38 to identify damaged or remodeled regions in a tissue.…”

Characterizing Tissue Remodeling and Mechanical Heterogeneity in Cerebral Aneurysms

“…To cluster the points into regions with similar deformative properties, edges with highest betweenness values were iteratively removed [18]. A network modularity was calculated for each grouping iteration, defined as the difference between the fraction of grouped elements and the fraction of grouped elements if the adjacency matrix weights were randomly assigned.…”

“…Since more heterogeneous tissues, such as diseased arteries, have more spatially heterogeneous strain distributions under an equibiaxial stretch, then more partitions are created by the partitioning scheme before modularity converges. The partitioning method has been validated in previous literature using an isotropic material with a single inclusion, in which 2 partitions were identified once modularity converged [18].…”