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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. 

BackgroundHealthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA). PurposeTo quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA. Study TypeRetrospective study. SubjectsFourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren‐Lawrence [KL] grade: 0; final KL grade: 3 over the 10‐year study). Field Strength/Sequence3.0‐T and 14.1‐T, biomechanics‐based displacement‐encoded imaging, fast spin echo, multi‐slice multi‐echoT2mapping. AssessmentWe studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades. Statistical TestsMultiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold atα = 0.05. ResultsGradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (R² = 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not. Data ConclusionSpatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early‐stage degeneration. Evidence Level1 Technical EfficacyStage 1