Development and validation of a computational model of the knee joint for the evaluation of surgical treatments for osteoarthritis

A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-...

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Bibliographic Details
Published in:Computer methods in biomechanics and biomedical engineering 2014-01, Vol.17 (13), p.1502-1517
Main Authors: Mootanah, R., Imhauser, C.W., Reisse, F., Carpanen, D., Walker, R.W., Koff, M.F., Lenhoff, M.W., Rozbruch, S.R., Fragomen, A.T., Dewan, Z., Kirane, Y.M., Cheah, K., Dowell, J.K., Hillstrom, H.J.
Format: Article
Language:English
Subjects:
Algorithms
Biomechanical Phenomena
Cartilage - physiology
Computer Simulation
Finite Element Analysis
Humans
in vitro cadaveric test
Knee Joint - anatomy & histology
Knee Joint - physiology
knee joint contact mechanics
lower limb malalignment
Magnetic Resonance Imaging
Male
Middle Aged
model validation
Models, Anatomic
osteoarthritis
Osteoarthritis - surgery
Pressure
Range of Motion, Articular
Rotation
subject-specific finite element knee model
Weight-Bearing
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Summary:A three-dimensional (3D) knee joint computational model was developed and validated to predict knee joint contact forces and pressures for different degrees of malalignment. A 3D computational knee model was created from high-resolution radiological images to emulate passive sagittal rotation (full-extension to 65°-flexion) and weight acceptance. A cadaveric knee mounted on a six-degree-of-freedom robot was subjected to matching boundary and loading conditions. A ligament-tuning process minimised kinematic differences between the robotically loaded cadaver specimen and the finite element (FE) model. The model was validated by measured intra-articular force and pressure measurements. Percent full scale error between FE-predicted and in vitro-measured values in the medial and lateral compartments were 6.67% and 5.94%, respectively, for normalised peak pressure values, and 7.56% and 4.48%, respectively, for normalised force values. The knee model can accurately predict normalised intra-articular pressure and forces for different loading conditions and could be further developed for subject-specific surgical planning.
ISSN:1025-5842
1476-8259
DOI:10.1080/10255842.2014.899588