1 research outputs found
Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation
Knee osteoarthritis (OA) is a painful joint disease,
causing disabilities in daily activities. However, there is no
known cure for OA, and the best treatment strategy might be
prevention. Finite element (FE) modeling has demonstrated
potential for evaluating personalized risks for the progression
of OA. Current FE modeling approaches use primarily
magnetic resonance imaging (MRI) to construct personalized
knee joint models. However, MRI is expensive and has lower
resolution than computed tomography (CT). In this study,
we extend a previously presented atlas-based FE modeling
framework for automatic model generation and simulation
of knee joint tissue responses using contrast agent-free CT. In
this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and
scaled to generate a personalized FE model. We compared
the simulated tissue responses of the CT-based models with
those of the MRI-based models. We show that the CT-based
models are capable of producing similar tensile stresses, fibril
strains, and fluid pressures of knee joint cartilage compared
to those of the MRI-based models. This study provides a new
methodology for the analysis of knee joint and cartilage
mechanics