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bioRxiv · 10.1101/2023.02.12.528211

Multi-frame biomechanical and relaxometry analysis during in vivo loading of the human knee by spiral dualMRI and compressed sensing

Lee, W.·Miller, E.·Zhu, H.·Schneider, S. E.·Reiter, D.·Neu, C. P.
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Abstract

PurposeKnee cartilage experiences repetitive loading during physical activities, which is altered during the pathogenesis of diseases like osteoarthritis. Analyzing the biomechanics during motion provides a clear understanding of the dynamics of cartilage deformation, and may establish essential imaging biomarkers of early-stage disease. However, in vivo biomechanical analysis of cartilage during rapid motion is not well established. MethodsWe used spiral DENSE MRI on in vivo human tibiofemoral cartilage during cyclic varus loading (0.5 Hz) and employed compressed sensing on the k-space data. The applied compressive load was set for each participant at 0.5x body weight on the medial condyle. Relaxometry methods were measured on the cartilage before (T1{rho}, T2) and after (T1{rho}) varus load. ResultsDisplacement and strain maps showed a gradual shift of displacement and strain in time. Compressive strain was observed in the medial condyle cartilage and shear strain was roughly half of the compressive strain. Male participants had more displacement in the loading direction compared to females, and T1{rho} values did not change after cyclic varus load. Compressed sensing reduced the scanning time up to 25-40% when comparing the displacement maps and substantially lowered the noise levels. ConclusionThese results demonstrated the ease of which spiral DENSE MRI could be applied to clinical studies due to the shortened imaging time, while quantifying realistic cartilage deformations that occur through daily activities, and that could serve as biomarkers of early osteoarthritis.

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Lee, W., Miller, E., Zhu, H., Schneider, S. E., Reiter, D., Neu, C. P.. 2023-02-12. Multi-frame biomechanical and relaxometry analysis during in vivo loading of the human knee by spiral dualMRI and compressed sensing. https://doi.org/10.1101/2023.02.12.528211

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