On the validity of using idealised sample geometries for interpreting mechanical tests of very soft tissues
2026-07-03 • Computational Engineering, Finance, and Science
Computational Engineering, Finance, and Science
AI summaryⓘ
The authors studied how using simplified shapes of brain tissue samples affects the measurement of their mechanical properties. They compared real sample shapes, obtained from MRI scans, to idealized cube shapes in computer models of tissue stretching and squishing tests. They found that the simplified shapes gave consistently lower estimates of tissue stiffness, especially in compression tests. This means using exact sample shapes is important for accurate results when studying soft tissues like the brain. The authors suggest avoiding geometry simplifications to prevent bias in such mechanical analyses.
inverse analysisconstitutive modelsshear modulusfinite element methodmagnetic resonance imaging (MRI)soft tissue mechanicssample geometryaxial loadingcompressive responsestrain distribution
Authors
Sajjad Arzemanzadeh, Karol Miller, Adam Wittek
Abstract
Mechanical characterisation of soft tissues often relies on inverse analysis of experimental data in which constitutive models are calibrated to match experimental force-displacement curves, yet the vast majority of such studies use idealised (nominal) sample geometries even though experimental samples unavoidably deviate from these nominal shapes because of imperfections in excision and mounting. The influence of these geometric simplifications on the material parameters determined through inverse analysis remains poorly quantified. We investigate the appropriateness of using idealised sample geometries in mechanical characterisation of brain tissue. Magnetic resonance imaging (MRI) was used to reconstruct the exact (real) geometry of each nominally cuboidal tissue sample. We determined a stress parameter (the shear modulus) by modelling, using the finite element method, tensile, compressive, and shear tests of brain tissue samples with both the MRI-based (real) and idealised cuboidal geometries, enabling a controlled comparison of geometry. Idealised geometries consistently yielded a lower stress parameter. The discrepancy in shear modulus between the real and idealised geometries varied across loading modes, averaging approximately 10% in shear and 48% under axial loading, predominantly arising from the compressive response. These discrepancies can be attributed to the inability of idealised-geometry models to accurately represent contact interactions and predict strain distributions, particularly under compressive loading. Idealisation of sample geometry may introduce systematic bias in the mechanical characterisation of very soft tissues; therefore, the actual measured sample geometry should be used in inverse analysis to identify constitutive models and their parameters.