3D Image Registration Marginally Improves the Precision of HR-pQCT Measurements Compared to Cross-Sectional-Area Registration in Adults With Osteogenesis Imperfecta
Bibliographic record
Abstract
Repositioning error in longitudinal high-resolution peripheral-quantitative computed tomography (HR-pQCT) imaging can lead to different bone volumes being assessed over time. To identify the same bone volumes at each time point, image registration is used. While cross-sectional area image registration corrects axial misalignment, 3D registration additionally corrects rotations. Other registration methods involving matched angle analysis (MA) or boundary transformations (3D-TB) can be used to limit interpolation error in 3D-registering micro-finite-element data. We investigated the effect of different image registration methods on short-term in vivo precision in adults with osteogenesis imperfecta, a collagen-related genetic disorder resulting in low bone mass, impaired quality, and increased fragility. The radii and tibiae of 29 participants were imaged twice on the same day with full repositioning. We compared the precision error of different image registration methods for density, microstructural, and micro-finite-element outcomes with data stratified based on anatomical site, motion status, and scanner generation. Regardless of the stratification, we found that image registration improved precision for total and trabecular bone mineral densities, trabecular and cortical bone mineral contents, area measurements, trabecular bone volume fraction, separation, and heterogeneity, as well as cortical thickness and perimeter. 3D registration marginally outperformed cross-sectional area registration for some outcomes, such as trabecular bone volume fraction and separation. Similarly, precision of micro-finite-element outcomes was improved after image registration, with 3D-TB and MA methods providing greatest improvements. Our regression model confirmed the beneficial effect of image registration on HR-pQCT precision errors, whereas motion had a detrimental effect on precision even after image registration. Collectively, our results indicate that 3D registration is recommended for longitudinal HR-pQCT imaging in adults with osteogenesis imperfecta. Since our precision errors are similar to those of healthy adults, these results can likely be extended to other populations, although future studies are needed to confirm this. © 2022 American Society for Bone and Mineral Research (ASBMR).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".