Knee Diameter and Cross-Sectional Area as Biomarkers for Cartilage Knee Degeneration on Magnetic Resonance Images.
Elias PrimetisDionysios DrakopoulosDominik SieronHugo MeusburgerKarol SzylukPaweł NiemiecVerena C ObmannAlan Arthur PetersAdrian T HuberLukas EbnerGeorgios DelimpasisAndreas ChristePublished in: Medicina (Kaunas, Lithuania) (2022)
Background and Objectives : Osteoarthritis (OA) of the knee is a degenerative disorder characterized by damage to the joint cartilage, pain, swelling, and walking disability. The purpose of this study was to assess whether demographic and radiologic parameters (knee diameters and knee cross-sectional area from magnetic resonance (MR) images) could be used as surrogate biomarkers for the prediction of OA. Materials and Methods : The knee diameters and cross-sectional areas of 481 patients were measured on knee MR images, and the corresponding demographic parameters were extracted from the patients' clinical records. The images were graded based on the modified Outerbridge arthroscopic classification that was used as ground truth. Receiver-operating characteristic (ROC) analysis was performed on the collected data. Results : ROC analysis established that age was the most accurate predictor of severe knee cartilage degeneration (corresponding to Outerbridge grades 3 and 4) with an area under the curve (AUC) of the specificity-sensitivity plot of 0.865 ± 0.02. An age over 41 years was associated with a sensitivity and specificity for severe degeneration of 82.8% (CI: 77.5-87.3%), and 76.4% (CI: 70.4-81.6%), respectively. The second-best degeneration predictor was the normalized knee cross-sectional area, with an AUC of 0.767 ± 0.04), followed by BMI (AUC = 0.739 ± 0.02), and normalized knee maximal diameter (AUC = 0.724 ± 0.05), meaning that knee degeneration increases with increasing knee diameter. Conclusions : Age is the best predictor of knee damage progression in OA and can be used as surrogate marker for knee degeneration. Knee diameters and cross-sectional area also correlate with the extent of cartilage lesions. Though less-accurate predictors of damage progression than age, they have predictive value and are therefore easily available surrogate markers of OA that can be used also by general practitioners and orthopedic surgeons.
Keyphrases
- total knee arthroplasty
- knee osteoarthritis
- cross sectional
- anterior cruciate ligament reconstruction
- magnetic resonance
- anterior cruciate ligament
- deep learning
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- convolutional neural network
- oxidative stress
- computed tomography
- chronic pain
- mass spectrometry
- spinal cord
- physical activity
- artificial intelligence
- big data
- neuropathic pain
- pain management