Readioff, R 
ORCID: 0000-0003-4887-9635, Seil, R ORCID: 0000-0001-8806-9384, Mouton, C, Marks, L and Barrera, O
(2023)
Image-based parametric finite element modelling for studying contact mechanics in human knee joints.
[Preprint]
Abstract
<jats:title>Abstract</jats:title><jats:sec><jats:title>Purpose</jats:title><jats:p>This study presents a framework for generating patient-specific finite element models, parameterised and optimised for contact mechanics from computed tomography (CT) scans, by avoiding the segmentation step usually employed to transform medical images into 3D models. Two morphological parameters affecting contact mechanics were investigated in the framework development: tibial cartilage thickness and tibial spine height. This study explores the effect of the interplay of these parameters in load sharing between meniscus and articulating cartilage, meniscal posterior and anterior roots strain and menisci kine-matics.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Morphological measurements from four knee CT scans were collected, such as the maximum thickness of the tibial cartilage (ranging from 1.1 to 5.2 mm), the height of the tibial spine (ranging from 3.55 to 10.1 mm), and the width of the tibial plateau in both the coronal (ranging from 27.3 to 36.17 mm) and sagittal (ranging from 31.79 to 53.77 mm) planes. These measurements were taken for the lateral tibial plateau for both left and right knees. Subsequently, three finite element (FE) models were generated, comprising lateral tibial plateaus, lateral femoral condyle and lateral meniscus. The tibial cartilage thickness was kept at a constant value of 1 mm while varying the tibial spine height within the range measured from the CT images. This resulted in three FE models with varying spine heights, categorised as large (height = 7.42 mm), medium (height = 4.25 mm), and small (height = 1.63 mm) tibial spine heights. The menisci in the FE models were generated to be congruent with the tibial plateau. For the first time, this study advances the representations of the knee menisci microstructure in FE modelling, such that we have generated meniscus FE models with three layers of a hyperelastic model in which layer thickness and layer-specific hyperelastic material parameters are derived from our previous experimental work.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The load sharing between the meniscus and articular cartilage was not sensitive to the varying tibial spine heights. In all three FE models, cartilage carried more than 90% of the applied load. However, the meniscus kinematics and root strains varied considerably with changing tibial spine heights. The small tibial spine height model predicted the highest meniscus movements (8.12 and 9.33 mm in the radial and circumferential directions, respectively) and the highest root strain (21.92 and 22.19 mm/mm in the anterior and posterior roots, respectively).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Our framework can generate finite element models of patients’ knees using clinical data (i.e., CT scans) without the need for lengthy image segmentation. This process is not only time-efficient but also independent of imaging operators. The models converge quickly (¿30 minutes on 2 cores) using an implicit solver with non-linear geometry and have the capability to predict contact mechanics between the articulating surfaces, meniscus kinematics and root strains. The modelling strategy presented here can provide valuable insights into predicting changes in the mechanics of soft tissues in the knee joint. It is particularly useful for investigating injury and surgical mechanisms related to the meniscus.</jats:p></jats:sec>
| Item Type: | Preprint |
|---|---|
| Uncontrolled Keywords: | Bioengineering, Biomedical Imaging, Musculoskeletal |
| Divisions: | Faculty of Science and Engineering > School of Engineering |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 25 Sep 2023 08:19 |
| Last Modified: | 15 Mar 2024 19:08 |
| DOI: | 10.1101/2023.09.07.556747 |
| Open Access URL: | https://www.biorxiv.org/content/10.1101/2023.09.07... |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3172993 |
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