MRI-based patient-specific nomogram for diagnostic risk stratification of patients with early knee osteoarthritis

Objectives This study is to develop a risk stratification nomogram for early-stage osteoarthritis (OA) based on magnetic resonance imaging (MRI), especially with potential sequences of MRI called T1rho and T2 mapping. Methods Cartilages diagnosed with early-stage OA or normal were collected and allocated into training or validation cohorts after the MRI. Eleven predictors were determined as candidate predictors for OA-anatomical signature-nomogram (OA-ASN). The performance of OA-ASN was evaluated using the concordance index (C-index), the area under the receiver operating characteristic curve (AUC), calibration plots, decision curve analysis (DCA), and clinical impact curve (CIC). Results A total of 199 patients were evaluated. Of these, 79 (39.7%) had early OA. infrapatellar fat pad (IPFP), T1 rho, and T2 mapping were independently associated with early-stage OA at multivariable analysis. The nomogram incorporating these variables displayed excellent discrimination (C-index, 0.975; 95% CI: 0.951, 0.999) in the training sample (n = 115) and bootstrap validation (C-index, 0.96), while C-index was 0.904 (95% CI: 0.840, 0.959) in the validation cohort (n = 84). The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. The DCA and CIC showed that the nomogram was clinically useful. Conclusions A smaller volume of IPFP, T1ρ value > 33, and T2 mapping > 35.04 were significantly associated with OA. The OA-ASN demonstrated excellent predictive outcomes with easy-accessible and simple observational screening methods based on physiological MRI, which can provide individual treatment strategies.