T2 Texture Analysis of Knee Cartilage in Healthy Individuals: Impact of Regular Running and Demographics
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.
Authors
- Dominik Vilímek (ORCID: https://orcid.org/0000-0003-3781-1280)
- Daniel Jandačka (ORCID: https://orcid.org/0000-0003-2653-2569)
- Vahid Ghodrati (ORCID: https://orcid.org/0000-0002-5964-333X)
- Miika T. Nieminen (ORCID: https://orcid.org/0000-0002-2300-2848)
- Jaroslav Uchytil (ORCID: https://orcid.org/0000-0002-0554-8943)
- Victor Casula (ORCID: https://orcid.org/0000-0003-0447-2796)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/0965
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00