Spatial patterning in the apparent density of subchondral bone can be used to discriminate between species that differ in their joint loading conditions. This study provides an experimental test of two hypotheses that relate aspects of subchondral apparent density patterns to joint loading conditions. First, the region of maximum subchondral apparent density (RMD) will correspond to differences in joint posture at the time of peak locomotor loads; and second, differences in maximum density between individuals will correspond to differences in exercise level. These hypotheses were tested using three age-matched samples of juvenile sheep. Two groups of five sheep were exercised, at moderate walking speeds, twice daily for 45 days on a treadmill with either a 0% or 15% grade. The remaining sheep were not exercised. Sheep walking on the inclined treadmill used more flexed knee postures than those in the level walking group at the time of peak vertical ground reaction forces. Kinematic measurements of knee posture were compared with knee postures estimated from the spatial position of the RMD on the medial femoral condyle. Our results show that the difference in the position of the RMD between the incline and level walking groups corresponded to the difference in knee postures obtained kinematically; however, exercised and nonexercised sheep did not differ in the magnitude of apparent density. These results suggest that patterns of subchondral apparent density are good indicators of the experimental modifications in joint posture during locomotion and may, therefore, be used to investigate differences between species in habitual joint loading.

Magnetic Resonance Imaging (MRI) longitudinal studies conducted to assess changes in tibia bone quality impose strict requirements on the reproducibility of the prescribed region acquired. Registration, the process of aligning two images, is commonly performed on the images after acquisition. However, techniques to improve image registration precision by adjusting scanning parameters prospectively, prior to image acquisition, would be preferred. We have adapted an automatic prospective mutual information based registration algorithm to a MRI longitudinal study of trabecular bone of the tibia and compared it to a post-scan manual registration. Qualitatively, image alignment due to the prospective registration is shown in 2D subtraction images and 3D surface renderings. Quantitatively, the registration performance is demonstrated by calculating the sum of the squares of the subtraction images. Results show that the sum of the squares is lower for the follow up images with prospective registration by an average of 19.37% +/- 0.07 compared to follow up images with post-scan manual registration. Our study found no significant difference between the trabecular bone structure parameters calculated from the post-scan manual registration and the prospective registration images (p > 0.05). All coefficient of variation values for all trabecular bone structure parameters were within a 2-4.5% range which are within values previously reported in the literature. Results suggest that this algorithm is robust enough to be used in different musculoskeletal imaging applications including the hip as well as the tibia.

This study investigated the feasibility of automatic image registration of MR high-spatial resolution proximal femur trabecular bone images as well as the effects of gray-level interpolation and volume of interest (VOI) misalignment on MR-derived trabecular bone structure parameters. For six subjects in a short-term study, a baseline scan and a follow-up scan of the proximal femur were acquired on the same day. For ten subjects in a long-term study, a follow-up scan of the proximal femur was acquired 1 year after the baseline. An automatic image registration technique, based on mutual information, utilized a baseline and a follow-up scan to compute transform parameters that aligned the two images. In the short-term study, these parameters were subsequently used to transform the follow-up image with three different gray-level interpolators. Nearest-neighbor interpolation and B-spline approximation did not significantly alter bone parameters, while linear interpolation significantly modified bone parameters (p<0.01). Improvement in image alignment due to the automatic registration for the long-term and short-term study was determined by inspecting difference images and 3D renderings. This work demonstrates the first application of automatic registration, without prior segmentation, of high-spatial resolution trabecular bone MR images of the proximal femur. Additionally, inherent heterogeneity in trabecular bone structure and imprecise positioning of the VOI along the slice (anterior-posterior) direction resulted in significant changes in bone parameters (p<0.01). Results suggest that automatic mutual information registration using B-spline approximation or nearest neighbor gray-level interpolation to transform the final image ensures VOI alignment between baseline and follow-up images and does not compromise the integrity of MR-derived trabecular bone parameters used in this study.

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