Dataset Information

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation.

ABSTRACT: 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 based on measurement of bone dimensions from native CT scans.

SUBMITTER: Mohammadi A

PROVIDER: S-EPMC7723937 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation.

Mohammadi Ali A Myller Katariina A H KAH Tanska Petri P Hirvasniemi Jukka J Saarakkala Simo S Töyräs Juha J Korhonen Rami K RK Mononen Mika E ME

Annals of biomedical engineering 20201111 12

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 tomogra ...[more]

PMID: 33179182

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Project description:PurposeTo compare multicomponent T2 parameters of the articular cartilage of the knee joint measured by using multicomponent driven equilibrium single-shot observation of T1 and T2 (mcDESPOT) in asymptomatic volunteers and patients with osteoarthritis.Materials and methodsThis prospective study was performed with institutional review board approval and with written informed consent from all subjects. The mcDESPOT sequence was performed in the knee joint of 13 asymptomatic volunteers and 14 patients with osteoarthritis of the knee. Single-component T2 (T2(Single)), T2 of the fast-relaxing water component (T2F) and of the slow-relaxing water component (T2S), and the fraction of the fast-relaxing water component (F(F)) of cartilage were measured. Wilcoxon rank-sum tests and multivariate linear regression models were used to compare mcDESPOT parameters between volunteers and patients with osteoarthritis. Receiver operating characteristic analysis was used to assess diagnostic performance with mcDESPOT parameters for distinguishing morphologically normal cartilage from morphologically degenerative cartilage identified at magnetic resonance imaging in eight cartilage subsections of the knee joint.ResultsHigher cartilage T2(Single) (P < .001), lower cartilage F(F) (P < .001), and similar cartilage T2F (P = .079) and T2S (P = .124) values were seen in patients with osteoarthritis compared with those in asymptomatic volunteers. Differences in T2(Single) and F(F) remained significant (P < .05) after consideration of age differences between groups of subjects. Diagnostic performance was higher with F(F) than with T2(Single) for distinguishing between normal and degenerative cartilage (P < .05), with greater areas under the curve at receiver operating characteristic analysis.ConclusionPatients with osteoarthritis of the knee had significantly higher cartilage T2(Single) and significantly lower cartilage F(F) than did asymptomatic volunteers, and receiver operating characteristic analysis results suggested that F(F) may allow greater diagnostic performance than that with T2(Single) for distinguishing between normal and degenerative cartilage.

Dataset Information

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation.

Publications

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation.

Similar Datasets

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