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Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking.

Annals of biomedical engineering2022Jahangir S, Mohammadi A, Mononen ME, et al.
Study designOther primary literature
SubjectHuman

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Study design
Other primary literature
Subject
Human
Publication year
2022
Source
doi.org
Abstract display
Shown here
Publication status
Corrected
Status checked
17 Aug 2026
Collected
4 Aug 2026
Freshness
Current
Review stage
Automated
Record status
Published

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Publication status: Corrected

Europe PMC relationship metadata: corrected_by.

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Abstract

Finite element (FE) modeling is becoming an increasingly popular method for analyzing knee joint mechanics and biomechanical mechanisms leading to osteoarthritis (OA). The most common and widely available imaging method for knee OA diagnostics is planar X-ray imaging, while more sophisticated imaging methods, e.g., magnetic resonance imaging (MRI) and computed tomography (CT), are seldom used. Hence, the capability to produce accurate biomechanical knee joint models directly from X-ray imaging would bring FE modeling closer to clinical use. Here, we extend our atlas-based framework by generating FE knee models from X-ray images (N = 28). Based on measured anatomical landmarks from X-ray and MRI, knee joint templates were selected from the atlas library. The cartilage stresses and strains of the X-ray-based model were then compared with the MRI-based model during the stance phase of the gait. The biomechanical responses were statistically not different between MRI- vs. X-ray-based models when the template obtained from X-ray imaging was the same as the MRI template. However, if this was not the case, the peak values of biomechanical responses were statistically different between X-ray and MRI models. The developed X-ray-based framework may pave the way for a clinically feasible approach for knee joint FE modeling.

MeSH

Biomechanical PhenomenaCartilage, ArticularFinite Element AnalysisHumansKnee JointOsteoarthritis, KneeWalkingX-Rays

DOI 10.1007/s10439-022-02941-0

PMID 35262835

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