Nonlinear Viscoelastic Properties of 3D-Printed Tissue Mimicking Materials and Metrics to Determine the Best Printed Material Match to Tissue Mechanical Behavior

Abstract

3D-printed biomaterials have become ubiquitous for clinical applications including tissue-mimicking surgical/procedure planning models and implantable tissue engineering scaffolds. In each case, a fundamental hypothesis is that printed material mechanical properties should match those of the tissue being replaced or modeled as closely as possible. Evaluating these hypotheses requires 1) consistent nonlinear elastic/viscoelastic constitutive model fits of 3D-printed biomaterials and tissues and 2) metrics to determine how well 3D-printed biomaterial mechanical properties match a corresponding tissue. Here we utilize inverse finite element modeling to fit nonlinear viscoelastic models with Neo-Hookean kernels to 29 Polyjet 3D-printed tissue-mimicking materials. We demonstrate that the viscoelastic models fit well with R2 > 0.95. We also introduce three metrics (least-squares difference, Kolmogorov–Smirnov statistics, and the area under stress/strain or load/displacement curve) to compare printed material properties to tissue properties. All metrics showed lower values for better matches between 3D-printed materials and tissues. These results provide a template for comparing 3D-printed material mechanical properties to tissue mechanical properties, and therefore, a basis for testing the fundamental hypotheses of 3D-printed tissue-mimicking materials.