The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Long term evaluation of disease progression through the quantitative magnetic resonance imaging of symptomatic knee osteoarthritis patients: correlation with clinical symptoms and radiographic changes
Open accessAbstract
The objective of this study was to further explore the cartilage volume changes in knee osteoarthritis (OA) over time using quantitative magnetic resonance imaging (qMRI). These were correlated with demographic, clinical, and radiological data to better identify the disease risk features. We selected 107 patients from a large trial (n = 1,232) evaluating the effect of a bisphosphonate on OA knees. The MRI acquisitions of the knee were done at baseline, 12, and 24 months. Cartilage volume from the global, medial, and lateral compartments was quantified. The changes were contrasted with clinical data and other MRI anatomical features. Knee OA cartilage volume losses were statistically significant compared to baseline values: -3.7 ± 3.0% for global cartilage and -5.5 ± 4.3% for the medial compartment at 12 months, and -5.7 ± 4.4% and -8.3 ± 6.5%, respectively, at 24 months. Three different populations were identified according to cartilage volume loss: fast (n = 11; -13.2%), intermediate (n = 48; -7.2%), and slow (n = 48; -2.3%) progressors. The predictors of fast progressors were the presence of severe meniscal extrusion (p = 0.001), severe medial tear (p = 0.005), medial and/or lateral bone edema (p = 0.03), high body mass index (p < 0.05, fast versus slow), weight (p < 0.05, fast versus slow) and age (p < 0.05 fast versus slow). The loss of cartilage volume was also slightly associated with less knee pain. No association was found with other Western Ontario McMaster Osteoarthritis Index (WOMAC) scores, joint space width, or urine biomarker levels. Meniscal damage and bone edema are closely associated with more cartilage volume loss. These data confirm the significant advantage of qMRI for reliably measuring knee structural changes at as early as 12 months, and for identifying risk factors associated with OA progression.
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Cites
Garnero, P., Piperno, M., Gineyts, E., Christgau, S., Delmas, P. D., & Vignon, E. (2001) · Annals of the Rheumatic Diseases · doi:10.1136/ard.60.6.619 · Cited by 475
Cited by
The Long-term Consequence of Anterior Cruciate Ligament and Meniscus Injuries: Osteoarthritis
Lohmander, L. S., Englund, P. M., Dahl, L. L., & Roos, E. M. (2007) · The American Journal of Sports Medicine · doi:10.1177/0363546507307396 · Cited by 2,344
Roemer, F. W., Guermazi, A., Javaid, M. K., Lynch, J. A., Niu, J., Zhang, Y., Felson, D. T., Lewis, C. E., Torner, J., & Nevitt, M. C. (2009) · Annals of the Rheumatic Diseases · doi:10.1136/ard.2008.096834 · Cited by 313
Advances in Imaging of Osteoarthritis and Cartilage
Roemer, F. W., Crema, M. D., Trattnig, S., & Guermazi, A. (2011) · Radiology · doi:10.1148/radiol.11101359 · Cited by 220
Deep convolutional neural network for segmentation of knee joint anatomy
Zhou, Z., Zhao, G., Kijowski, R., & Liu, F. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27229 · Cited by 202
Machine-learning-based patient-specific prediction models for knee osteoarthritis
Jamshidi, A., Pelletier, J.-P., & Martel-Pelletier, J. (2019) · Nature Reviews Rheumatology · doi:10.1038/s41584-018-0130-5 · Cited by 190
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Metadata
- Authors
- Raynauld, J.-P., Martel-Pelletier, J., Berthiaume, M.-J., Beaudoin, G., Choquette, D., Haraoui, B., Tannenbaum, H., Meyer, J. M., Beary, J. F., Cline, G. A., & Pelletier, J.-P.
- Venue
- Arthritis Research & Therapy
- Published
- 2005-12-30
- Volume
- 8
- Issue
- 1
- Pages
- R21-R21
- ISSN
- 1478-6354 (ISSN-L)
- OpenAlex
- W2162077957
- Cited by
- 259
- References
- 1
- FWCI
- 9.39
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Long term evaluation of disease progression through the quantitative magnetic resonance imaging of symptomatic knee osteoarthritis patients: correlation with clinical symptoms and radiographic changes. https://app.cochat.ai/papers/10.1186/ar1875
- The paper
- Raynauld, J.-P., Martel-Pelletier, J., Berthiaume, M.-J., Beaudoin, G., Choquette, D., Haraoui, B., Tannenbaum, H., Meyer, J. M., Beary, J. F., Cline, G. A., & Pelletier, J.-P. (2005). Long term evaluation of disease progression through the quantitative magnetic resonance imaging of symptomatic knee osteoarthritis patients: correlation with clinical symptoms and radiographic changes. Arthritis Research & Therapy. https://doi.org/10.1186/ar1875
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
