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Intervertebral disc (IVD) degeneration is a significant health issue that can lead to severe complications. Recent research has highlighted the close relationship between disc degeneration and the biomechanical properties of the IVD. This study introduces an innovative approach—magnetic resonance imaging (MRI) elastography of the human IVD—using an explicit inverse solver to identify the non-homogeneous shear modulus map of the IVD. The key advantage of this explicit solver is its streamlined optimization process, focusing only on the shear moduli of the nucleus pulposus (NP), annulus fibrosus (AF), and their interface. This approach reduces the optimization variables, making it more efficient than traditional pixel-based approaches. To validate this method, we conducted a plane strain numerical example, observing a consistent underestimation of the AF/NP shear modulus ratio by a scaling factor of approximately 1.5. Further investigations included comprehensive sensitivity analyses to various noise levels, revealing that the proposed method accurately characterizes shear modulus distribution in the AF and NP regions, with a maximum relative error of the AF/NP shear modulus ratio remaining below 8%. In addition, applying this approach to real human IVDs underin vitrocompression or bending, demonstrated its effectiveness, yielding an AF/NP shear modulus ratio within a reasonable range of 6–15. In summary, the proposed method offers a promising direction for MRI elastography of the human IVD. 

Abstract This paper presents a method to derive the virtual fields for identifying constitutive model parameters using the Virtual Fields Method (VFM). The VFM is an approach to identify unknown constitutive parameters using deformation fields measured across a given volume of interest. The general principle for solving identification problems with the VFM is first to derive parametric stress field, where the stress components at any point depend on the unknown constitutive parameters, across the volume of interest from the measured deformation fields. Applying the principle of virtual work to the parametric stress fields, one can write scalar equations of the unknown parameters and solve the obtained system of equations to deduce the values of unknown parameters. However, no rules have been proposed to select the virtual fields in identification problems related to nonlinear elasticity and there are multiple strategies possible that can yield different results. In this work, we propose a systematic, robust and automatic approach to reconstruct the systems of scalar equations with the VFM. This approach is well suited to finite-element implementation and can be applied to any problem provided that full-field deformation data are available across a volume of interest. We also successfully demonstrate the feasibility of the novel approach by multiple numerical examples. Potential applications of the proposed approach are numerous in biomedical engineering where imaging techniques are commonly used to observe soft tissues and where alterations of material properties are markers of diseased states.