Detection of maturity and ligament injury using magic angle directional imaging

Purpose: To investigate whether magnetic field–related anisotropies of collagen may be correlated with postmortem findings in animal models. Methods: Optimized scan planning and new MRI data‐processing methods were proposed and analyzed using Monte Carlo simulations. Six caprine and 10 canine knees were scanned at various orientations to the main magnetic field. Image intensities in segmented voxels were used to compute the orientation vectors of the collagen fibers. Vector field and tractography plots were computed. The Alignment Index was defined as a measure of orientation distribution. The knees were subsequently assessed by a specialist orthopedic veterinarian, who gave a pathological diagnosis after having dissected and photographed the joints. Results: Using 50% less scans than reported previously can lead to robust calculation of fiber orientations in the presence of noise, with much higher accuracy. The 6 caprine knees were found to range from very immature ( 3 years). Mature specimens exhibited significantly more aligned collagen fibers in their patella tendons compared with the immature ones. In 2 of the 10 canine knees scanned, partial cranial caudal ligament tears were identified from MRI and subsequently confirmed with encouragingly high consistency of tractography, Alignment Index, and dissection results. Conclusion: This method can be used to detect injury such as partial ligament tears, and to visualize maturity‐related changes in the collagen structure of tendons. It can provide the basis for new, noninvasive diagnostic tools in combination with new scanner configurations that allow less‐restricted field orientations

Evaluating automated dynamic contrast enhanced wrist 3T MRI in healthy volunteers: one-year longitudinal observational study.

RATIONAL AND OBJECTIVE: Dynamic contrast enhanced (DCE)-MRI has great potential to provide quantitative measure of inflammatory activity in rheumatoid arthritis. There is no current benchmark to establish the stability of signal in the joints of healthy subjects when imaged with DCE-MRI longitudinally, which is crucial so as to differentiate changes induced by treatment from the inherent variability of perfusion measures. The objective of this study was to test a pixel-by-pixel parametric map based approach for analysis of DCE-MRI (Dynamika) and to investigate the variability in signal characteristics over time in healthy controls using longitudinally acquired images. MATERIALS AND METHODS: 10 healthy volunteers enrolled, dominant wrists were imaged with contrast enhanced 3T MRI at baseline, week 12, 24 and 52 and scored with RAMRIS, DCE-MRI was analysed using a novel quantification parametric map based approach. Radiographs were obtained at baseline and week 52 and scored using modified Sharp van der Heidje method. RAMRIS scores and dynamic MRI measures were correlated. RESULTS: No erosions were seen on radiographs, whereas MRI showed erosion-like changes, low grade bone marrow oedema and low-moderate synovial enhancement. The DCE-MRI parameters were stable (baseline scores, variability) (mean±st.dev); in whole wrist analysis, MEmean (1.3±0.07, -0.08±0.1 at week 24) and IREmean (0.008±0.004, -0.002±0.005 at week 12 and 24). In the rough wrist ROI, MEmean (1.2±0.07, 0.04±0.02 at week 52) and IREmean (0.001±0.0008, 0.0006±0.0009 at week 52) and precise wrist ROI, MEmean (1.2±0.09, 0.04±0.04 at week 52) and IREmean (0.001±0.0008, 0.0008±0.001 at week 24 and 52). The Dynamic parameters obtained using fully automated analysis demonstrated strong, statistically significant correlations with RAMRIS synovitis scores. CONCLUSION: The study demonstrated that contrast enhancement does occur in healthy volunteers but the inherent variability of perfusion measures obtained with quantitative DCE-MRI method is low and stable, suggesting its suitability for longitudinal studies of inflammatory arthritis. These results also provide important information regarding potential cut-off levels for imaging remission goals in patients with RA using both RAMRIS and DCE-MRI extracted parametric parameters