Multi-component 3D-T1ρ Mapping of Early Knee Osteoarthritis

Motivation: Multi-component models for quantitative knee cartilage mapping often compare individual parameters between groups, discarding the relationship between parameters. Goal(s): Evaluate the performance of linear combinations of the multi-component parameters into a single composite biomarker for early knee osteoarthritis (OA). Approach: Seven T1ρ-weighted images were acquired for two groups, one consisting of 17 healthy subjects and another consisting of 27 early knee OA patients. These images were used to fit three different exponential models. Receiver operating characteristic (ROC) and area under the curve (AUC) were then assessed to evaluate the sensitivity of each model. Results: The combined biomarkers outperformed mono-exponential T1ρ in AUC. Impact: The study shows that combining multi-component MRI parameters into a single composite biomarker can enhance diagnostic performance and outperform mono-exponential T1ρ analysis. Our proposed approach has broader potential for improving early OA detection and assessment of other diseases.