alexa Femorotibial and patellar cartilage loss in patients prior to total knee arthroplasty, heterogeneity, and correlation with alignment of the knee.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): von EisenhartRothe R, Graichen H, Hudelmaier M, Vogl T, Sharma L,

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Abstract OBJECTIVE: To analyse tibial, femoral, and patellar cartilage loss in patients prior to total knee arthroplasty (TKA), and its correlation with alignment of the knee. METHODS: 26 patients (aged 58 to 86 years) with a clinical indication for TKA were investigated. Quantitative end points of cartilage morphology (T scores for cartilage volume normalised to total subchondral bone area) were determined from coronal and axial magnetic resonance image data, using proprietary software. The static alignment of the knee was determined from standing full limb radiographs. RESULTS: The magnitude of cartilage loss (T score of normalised cartilage volume) was highly variable within the knee, correlation coefficients ranging from r = 0.17 to 0.51 between cartilage plates. The correlation of cartilage loss with static alignment of the knee (as a continuous variable) was r = -0.52 (p<0.05) for the medial tibia, -0.38 (not significant) for the medial femur, +0.76 (p<0.001) for the lateral tibia, +0.31 (not significant) for the lateral femur, and -0.09 for the patella. When analysing alignment independent of direction (valgus or varus), the correlation for the patella increased to r = 0.30, but remained non-significant. CONCLUSIONS: Cartilage loss was highly variable among patients and among cartilage plates before knee arthroplasty. Its correlation with alignment was stronger for the tibia than for the femur. There was some evidence for an association of alignment and patellar cartilage loss. These findings stimulate further research on the mechanism and cause-effect relation of alignment and knee osteoarthritis using quantitative magnetic resonance imaging technology.
This article was published in Ann Rheum Dis and referenced in Journal of Computer Science & Systems Biology

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