Objective

The purpose of this work was to review the current literature on cartilage and meniscal T2 relaxation time.

Methods

Electronic searches in PubMed were performed to identify relevant studies about T2 relaxation time measurements as non-invasive biomarker for knee osteoarthritis (OA) and cartilage repair procedures.

Results

Initial osteoarthritic changes include proteoglycan loss, deterioration of the collagen network, and increased water content within the articular cartilage and menisci. T2 relaxation time measurements are affected by these pathophysiological processes. It was demonstrated that cartilage and meniscal T2 relaxation time values were significantly increased in subjects with compared to those without radiographic OA and focal knee lesions, respectively. Subjects with OA risk factors such as overweight/obesity showed significantly greater cartilage T2 values than normal controls. Elevated cartilage and meniscal T2 relaxation times were found in subjects with vs without knee pain. Increased cartilage T2 at baseline predicted morphologic degeneration in the cartilage, meniscus, and bone marrow over 3 years. Furthermore, cartilage repair tissue could be non-invasively assessed by using T2 mapping. Reproducibility errors for T2 measurements were reported to be smaller than the T2 differences in healthy and diseased cartilage indicating that T2 relaxation time may be a reliable discriminatory biomarker.

Conclusions

Cartilage and meniscal T2 mapping may be suitable as non-invasive biomarker to diagnose early stages of knee OA and to monitor therapy of OA.

Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage

Summary

The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone.

Introduction

An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique.

Methods

One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter.

Results

The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone.

Conclusion

A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.