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Abstract #0965

T2 Texture Analysis of Knee Cartilage in Healthy Individuals: Impact of Regular Running and Demographics

Vahid Ghodrati1, Dominik Vilimek2, Jaroslav Uchytil3, Daniel Jandacka3, Miika T Nieminen1,4, and Victor Casula1
1Research Unit of Health Sciences and Technology, University of Oulu, Oulu, FINLAND, Oulu, Finland, 2Department of Cybernetics and Biomedical Engineering, VSB Technical University of Ostrava, Ostrava, CZECH REPUBLIC, Ostrava, Czech Republic, 3Department of Human Movement Studies, University of Ostrava, Ostrava, CZECH REPUBLIC, Ostrava, Czech Republic, 4Department of Diagnostics, Oulu University Hospital, Oulu, FINLAND, Oulu, Finland

Synopsis

Keywords: Cartilage, MSK, Cartilage

Motivation: To explore early detection of articular cartilage degeneration using quantitative MRI (qMRI), physical activity and demographic factors.

Goal(s): To investigate the relationship between demographic characteristics, regular running, and GLCM texture features in T2-maps of the tibiofemoral cartilage in a large cohort of healthy adults.

Approach: A cohort of 1,214 healthy participants underwent T2-mapping MRI, with texture features analyzed using multivariate regression models that accounted for sex, age, BMI, and running distance.

Results: Significant texture variations were associated with male sex, older age, overweight and obesity, and high weekly running distances, suggesting early degeneration similar to OA patients and the need for targeted interventions.

Impact: These results may advance machine learning models using non-invasive T2 texture analysis to identify osteoarthritis risk, promoting research into preventive strategies and enhancing monitoring and early interventions for joint health through improved understanding of cartilage changes.

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