Impact of walking on knee articular cartilage T2 values estimated with a dictionary-based approach - A pilot study

Abstract

Introduction: Walking is crucial for knee articular cartilage (KAC) health. Routine MRI sequences lack sensitivity for early cartilage changes, and the use of parametric T2 maps to study the effect of walking on KAC composition is limited. This study aimed to evaluate if quantitative T2 maps using an Echo Modulation Curve (EMC) matching algorithm can detect KAC T2 variations due to water content changes after walking.

Methods: Seven asymptomatic volunteers (3 females, 4 males, mean age 28.3 years) without knee pathologies participated. Sagittal knee MRI scans were performed before and after a 9-min treadmill walk using a Modified Bruce protocol. T2-weighted Multi-Echo Spin-Echo KAC images were acquired at 3T. Tibiofemoral cartilage was segmented semi-automatically on three slices per knee, defining 39 KAC samples. Quantitative T2 maps were created using a dictionary-matching algorithm. Paired t-tests assessed exercise impact on KAC T2 values, independent t-tests compared group differences, and Friedman test with Bonferroni correction evaluated regional T2 changes.

Results: Walking increased KAC T2 values (mean difference (md) 0.61 ± 1.71 ms; p = 0.016). Significant differences were observed in ""normal"" BMI group (md 0.69 ± 1.27 ms; p = 0.021). Regional analysis revealed significant differences in medial femur in males (md 0.9 ± 2.1 ms; p = 0.049) and lateral tibia in females (md 1.4 ± 2.5 ms; p = 0.046). The medial tibia showed significant differences across sub-regions (p = 0.026).

Conclusion: Quantitative T2 maps using the EMC matching algorithm detected consistent changes in KAC T2 values after a short walking period.

Implications for practice: EMC quantitative T2 maps effectively detected knee cartilage changes post-walking. This technique could improve cartilage hydration assessments, aiding early detection in at-risk patients. It also suggests potential for personalized monitoring and rehabilitation, advancing musculoskeletal imaging and non-invasive joint health monitoring.