Sustained tissue compression can lead to pressure ulcers, which can either start superficially or within deeper tissue layers. The latter type includes deep tissue injury, starting in skeletal muscle underneath an intact skin. Since the underlying damage mechanisms are poorly understood, prevention and early detection are difficult. Recent in vitro studies and in vivo animal studies have suggested that tissue deformation per se can lead to damage. In order to conclusively couple damage to deformation, experiments are required in which internal tissue deformation and damage are both known. Magnetic resonance (MR) tagging and T2-weighted MR imaging can be used to measure tissue deformation and damage, respectively, but they cannot be combined in a protocol for measuring damage after prolonged loading. Therefore, a dedicated finite element model was developed to calculate strains in damage experiments. In the present study, this model, which describes the compression of rat skeletal muscles, was validated with MR tagging. Displacements from both the tagging experiments and the model were interpolated on a grid and subsequently processed to obtain maximum shear strains. A correlation analysis revealed a linear correlation between experimental and numerical strains. It was further found that the accuracy of the numerical prediction decreased for increasing strains, but the positive predictive value remained reasonable. It was concluded that the model was suitable for calculating strains in skeletal muscle tissues in which damage is measured due to compression.
Validation of a Numerical Model of Skeletal Muscle Compression With MR Tagging: A Contribution to Pressure Ulcer Research
Ceelen, K. K., Stekelenburg, A., Mulders, J. L. J., Strijkers, G. J., Baaijens, F. P. T., Nicolay, K., and Oomens, C. W. J. (October 23, 2008). "Validation of a Numerical Model of Skeletal Muscle Compression With MR Tagging: A Contribution to Pressure Ulcer Research." ASME. J Biomech Eng. December 2008; 130(6): 061015. https://doi.org/10.1115/1.2987877
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