Partial-thickness rotator cuff tendon tears are a prevalent cause of pain and disability, affecting 13–32% of the general population. Despite the clinical significance, the natural progression of these tears remains poorly understood. Surgical intervention is generally recommended when more than 50% of tendon thickness is involved—a threshold based primarily on anecdotal evidence. Furthermore, re-tear rates after repair can be as high as 35%, underscoring the need for improved characterization and targeted treatment strategies. To address these gaps, my laboratory has pioneered a soft-tissue characterization approach that integrates full-field kinematic measurement with inverse methods to determine material properties. Building on successful application to soft tissues and elastomers, we have developed a custom displacement-encoded MRI protocol, in which the phase of each voxel (modulo 2π) directly quantifies displacement during tendon stretching. This enables acquisition of the entire three-dimensional displacement field of the rotator cuff tendon at sub-millimeter resolution. We couple these high-resolution imaging data with a novel variational system identification (VSI) method, deployed for the first time on soft tissue. VSI enables systematic inference of the most parsimonious and physically meaningful material models. Applying this approach to both intact and partially torn rotator cuff tendons, we observe distinct differences in shear strain distributions, particularly elevated shear within the interior of partially torn tendons—features that traditional surface-based measurements cannot capture. These findings suggest delamination (mode II failure) as a key mechanism in tear progression, with direct implications for surgical strategy and risk of retear. We further demonstrate that anatomical differences influence strain patterns, strengthening the case for personalized, data-driven approaches such as digital twins. These digital replicas, generated using high-resolution MRI-derived geometry, could inform surgeon decisions regarding tear management and suture placement to minimize retear risk. The rotator cuff tendon’s complex anisotropic, elastic behavior is modeled within the VSI framework via strain energy density functions based on polynomial invariants. This integrated experimental and computational platform offers unprecedented insight intorotator cuff tendon mechanics and has the potential to improve clinical outcomes through
personalized surgical planning.