Objective

Quantitative T1ρ MRI has been suggested as a promising tool to detect changes in cartilage composition that are characteristic of cartilage damage and degeneration. The objective of this study was to evaluate the capability of MR T1ρ to detect cartilage lesions as evaluated by arthroscopy in acutely ACL-injured knees and to compare with the Whole-Organ Magnetic Resonance Imaging Score (WORMS) using clinical standard MRI.

Method

Ten healthy controls (mean age 35) with no ACL injury or history of osteoarthritis (OA) and 10 patients with acute ACL injuries (mean age 39) were scanned at 3 Tesla (3T). ACL patients underwent ACL reconstruction, where focal lesions were graded according to an Outerbridge grading system during arthroscopic evaluation. Normalized MR T1ρ values (T1ρ z-scores normalized to control values in matched regions) in full thickness, and superficial and deep layers of cartilage were compared between defined sub-compartments with and without focal lesions. Intraclass (ICC) correlation and the root mean square coefficient of variation (RMS-CV) were performed to evaluate the inter-observer reproducibility of T1ρ quantification. Sub-compartments of cartilage were also evaluated using WORMS scoring and compared to their Outerbridge score respectively.

Results

The inter-observer ICC and the RMS-CV of the sub-compartment T1ρ quantification were 0.961 and 3.9%, respectively. The average T1ρ z-scores were significantly increased in sub-compartments with focal lesions compared to those without focal lesions and to the control cohort (p<0.05).

Conclusion

Our results indicate that T1ρ provided a better diagnostic capability than clinical standard MRI grading in detecting focal cartilage abnormalities after acute injuries. Quantitative MRI may have great potential in detecting cartilage abnormalities and degeneration non-invasively, which are occult with standard morphological MRI.

In this technique development study, high-resolution peripheral quantitative computed tomography (HR-pQCT) was applied to non-invasively image and quantify 3D joint space morphology of the wrist and metacarpophalangeal (MCP) joints of patients with rheumatoid arthritis (RA). HR-pQCT imaging (82 μm voxel-size) of the dominant hand was performed in patients with diagnosed rheumatoid arthritis (RA, N = 16, age: 52.6 ± 12.8) and healthy controls (CTRL, N = 7, age: 50.1 ± 15.0). An automated computer algorithm was developed to segment wrist and MCP joint spaces. The 3D distance transformation method was applied to spatially map joint space width, and summarized by the mean joint space width (JSW), minimal and maximal JSW (JSW.MIN, JSW.MAX), asymmetry (JSW.AS), and distribution (JSW.SD)-a measure of joint space heterogeneity. In vivo precision was determined for each measure by calculating the smallest detectable difference (SDD) and root mean square coefficient of variation (RMSCV%) of repeat scans. Qualitatively, HR-pQCT images and pseudo-color JSW maps showed global joint space narrowing, as well as regional and focal abnormalities in RA patients. In patients with radiographic JSN at an MCP, JSW.SD was two-fold greater vs. CTRL (p < 0.01), and JSW.MIN was more than two-fold lower (p < 0.001). Similarly, JSW.SD was significantly greater in the wrist of RA patients vs. CTRL (p < 0.05). In vivo precision was highest for JSW (SDD: 100 μm, RMSCV: 2.1%) while the SDD for JSW.MIN and JSW.SD were 370 and 110 μm, respectively. This study suggests that in vivo quantification of 3D joint space morphology from HR-pQCT, could improve early detection of joint damage in rheumatological diseases.