Validation of a Finite Element Simulation for Predicting Individual Knee Joint Kinematics.
Elin TheilenAnna RorichThomas LangeSebastian BendakCora HuberHagen SchmalKaywan IzadpanahJoachim GeorgiiPublished in: IEEE open journal of engineering in medicine and biology (2023)
Goal: We introduce an in-vivo validated finite element (FE) simulation approach for predicting individual knee joint kinematics. Our vision is to improve clinicians' understanding of the complex individual anatomy and potential pathologies to improve treatment and restore physiological joint kinematics. Methods: Our 3D FE modeling approach for individual human knee joints is based on segmentation of anatomical structures extracted from routine static magnetic resonance (MR) images. We validate the predictive abilities of our model using static MR images of the knees of eleven healthy volunteers in dedicated knee poses, which are achieved using a customized MR-compatible pneumatic loading device. Results: Our FE simulations reach an average translational accuracy of 2 mm and an average angular accuracy of 1[Formula: see text] compared to the reference knee pose. Conclusions: Reaching high accuracy, our individual FE model can be used in the decision-making process to restore knee joint stability and functionality after various knee injuries.
Keyphrases
- finite element
- magnetic resonance
- total knee arthroplasty
- anterior cruciate ligament
- deep learning
- knee osteoarthritis
- contrast enhanced
- convolutional neural network
- decision making
- anterior cruciate ligament reconstruction
- endothelial cells
- computed tomography
- optical coherence tomography
- palliative care
- high resolution
- preterm infants
- machine learning
- molecular dynamics
- climate change
- mass spectrometry
- risk assessment
- human health
- induced pluripotent stem cells