Detection of Early Knee Osteoarthritis Using Multi-Component T_1ρ Mapping

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.

To evaluate if stretched- (SE) and bi-exponential (BE) T_1ρ models can improve early knee OA detection over the ME model.

Case-control study.

Twenty-six healthy subjects (mean age 51.5) and 26 early knee OA patients (mean age 61.8).

T_1ρ-prepared Turbo FLASH sequence at 3 T field strength.

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.

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.

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).

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.

4.

Stage 2.