Abstract
BACKGROUND: Early detection of knee osteoarthritis (OA) is important. Spin-lattice relaxation in the rotating frame (T(1ρ)) mapping is sensitive to early cartilage changes, but the mono-exponential (ME) model may be limited. Multi-component models can capture more tissue complexity, but their diagnostic advantage has not been validated. PURPOSE: To evaluate if stretched- (SE) and bi-exponential (BE) T(1ρ) models can improve early knee OA detection over the ME model. STUDY TYPE: Case-control study. POPULATION: Twenty-six healthy subjects (mean age 51.5) and 26 early knee OA patients (mean age 61.8). FIELD STRENGTH/SEQUENCE: T(1ρ)-prepared Turbo FLASH sequence at 3 T field strength. ASSESSMENT: T(1ρ) parameters from three exponential models were adjusted for age. To maximize group separability, the parameters were combined into single discriminators for both global knee cartilage and six anatomical sub-regions. Diagnostic performance was assessed based on the ability of these combined models to distinguish early OA. STATISTICAL TESTS: Parameters were adjusted for age. Mann-Whitney U-test (group comparisons), linear discriminant analysis (LDA), and area under the receiver operating characteristic (ROC) curve (AUC) with bootstrapped 95% confidence intervals (CI). Significance level set at p < 0.05, using the false discovery rate (FDR) to correct for multiple comparisons. RESULTS: In the global analysis, no model demonstrated significant diagnostic performance (p-values of 0.63, 0.96, 0.63 for ME, SE, and BE). Multi-regional SE model (AUC = 0.83, CI: 0.72, 0.93) significantly distinguished OA and healthy groups. Calibration analysis showed the SE model had the lowest Brier score (0.17), significantly better than the ME model (0.26). DATA CONCLUSION: Sub-regional analysis of T(1ρ) parameter maps suggests an improvement in diagnostic performance for early knee OA compared to globally averaged measurements. The stretched-exponential model showed the most promise. However, small sample size and wide confidence intervals highlight the need for further validation with a larger cohort before clinical utility claims can be made. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.