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Identifying and diagnosing early-stage rheumatoid arthritis (RA) has remained an unmet challenge in medicine and a roadblock to identifying treatments at time points when disease-modifying therapies may be most effective. Recent studies have demonstrated that imaging the response of cartilage under mechanical loading, as well as alterations in matrix macro- and micro-molecule composition, could serve as potential biomarkers to identify tissue degeneration. Therefore, the objective of this paper was to identify RA-related cartilage degeneration in human wrists using novel MRI techniques. We applied in vivo displacement-encoded MRI to human wrists during cyclic radioulnar deviation, along with the quantitative MRI methods (T1ρ, T2, T2*) during a static condition, to a small healthy and RA patient cohort (6 healthy, 4 RA). We then used a linear mixed-effects model to identify key factors affecting the results. We found that the RA patients had wrists with higher torsional stiffness by approximately 2-fold compared to the control group. The RA group showed lower intercarpal joint displacements by roughly half of the control group, and some joint regions indicated tissue softening. We also found that the quantitative MRI metrics showed non-significant differences between control and RA groups (the T2 and T2* of the RA group was roughly 10% and 5% more than the control group, respectively), however, differences were detected among regions in T2 and T2* metrics. This study demonstrated that displacement-encoded MRI may be a promising method to distinguish functional and noninvasive metrics between RA and healthy wrists, and may provide a means to distinguish the disease state compared to conventional imaging methods.
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http://dx.doi.org/10.1038/s41598-025-17316-3 | DOI Listing |
Sci Rep
September 2025
Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, 1111 Engineering Drive, UCB 427, Boulder, CO, 80309, USA.
Identifying and diagnosing early-stage rheumatoid arthritis (RA) has remained an unmet challenge in medicine and a roadblock to identifying treatments at time points when disease-modifying therapies may be most effective. Recent studies have demonstrated that imaging the response of cartilage under mechanical loading, as well as alterations in matrix macro- and micro-molecule composition, could serve as potential biomarkers to identify tissue degeneration. Therefore, the objective of this paper was to identify RA-related cartilage degeneration in human wrists using novel MRI techniques.
View Article and Find Full Text PDFMagn Reson Med
March 2025
School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Purposes: To enhance the functional capability of MRI, this study aims to develop a novel MR elastography (MRE) sequence that achieves rapid acquisition without distortion artifacts.
Methods: A displacement-encoded stimulated echo (DENSE) with multiphase acquisition scheme was used to capture wave images. A center-out golden-angle stack-of-stars sampling pattern was introduced for improved SNR and data incoherence.
bioRxiv
September 2023
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
Intervertebral disc degeneration is the most recognized cause of low back pain, characterized by the decline of tissue structure and mechanics. Image-based mechanical parameters (e.g.
View Article and Find Full Text PDFRadiol Cardiothorac Imaging
June 2023
From the Department of Biomedical Engineering, University of Virginia, Biomedical Engineering and Medical Science Building, Room 2013, MR5, Charlottesville, VA 22903 (Y.W., C.S., S.G., D.C.A., F.H.E.); Department of Biomedical, Biological and Chemical Engineering and Department of Radiology, Univers
J Magn Reson Imaging
July 2023
Paul M. Rady Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado, USA.
Background: Healthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA).
Purpose: To quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA.