PURPOSE: To evaluate an automatic 3D registration algorithm for serial high-resolution images of trabecular bone (TB) in studies designed to evaluate the response of the trabecular architecture to intervention or disease progression. MATERIALS AND METHODS: An efficient algorithm for registering high-resolution 3D images of TB is presented. The procedure identifies the six parameters of rigid displacement between two scans performed at different timepoints. By assuming a relatively small through-plane rotation, considerable time is saved by combining the results of a collection of regional 2D registrations throughout the TB region of interest (ROI). The algorithm was applied to 26 pairs of MR images acquired 6 months apart. Reproducibility of local TB structural parameters (plate, rod, and junction density) computed in manually selected regions were compared between baseline and registered follow-up images. RESULTS: All 26 registrations were completed successfully in less than 30 seconds per image pair. The resampled follow-up images agreed with baseline to around one pixel throughout the volume at 137 x 137 x 410 microm(3) image resolution. Structural parameters in each region correlated well from baseline to follow-up with intraclass correlation coefficients ranging between 85%-97% for TB plate density. Interregional variations in the parameters were large as compared with intraregion reproducibility. CONCLUSION: The proposed algorithm was successful in automatically registering baseline and follow-up TB images in a translational study, and may be useful in regional analyses in longitudinal MR studies of TB architecture.
PURPOSE: To evaluate an automatic 3D registration algorithm for serial high-resolution images of trabecular bone (TB) in studies designed to evaluate the response of the trabecular architecture to intervention or disease progression. MATERIALS AND METHODS: An efficient algorithm for registering high-resolution 3D images of TB is presented. The procedure identifies the six parameters of rigid displacement between two scans performed at different timepoints. By assuming a relatively small through-plane rotation, considerable time is saved by combining the results of a collection of regional 2D registrations throughout the TB region of interest (ROI). The algorithm was applied to 26 pairs of MR images acquired 6 months apart. Reproducibility of local TB structural parameters (plate, rod, and junction density) computed in manually selected regions were compared between baseline and registered follow-up images. RESULTS: All 26 registrations were completed successfully in less than 30 seconds per image pair. The resampled follow-up images agreed with baseline to around one pixel throughout the volume at 137 x 137 x 410 microm(3) image resolution. Structural parameters in each region correlated well from baseline to follow-up with intraclass correlation coefficients ranging between 85%-97% for TB plate density. Interregional variations in the parameters were large as compared with intraregion reproducibility. CONCLUSION: The proposed algorithm was successful in automatically registering baseline and follow-up TB images in a translational study, and may be useful in regional analyses in longitudinal MR studies of TB architecture.
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