Technical note: Mapping of trabecular bone anisotropy and volume fraction in <scp>3D</scp> using <scp>μCT</scp> images of the human calcaneus
Bibliographic record
Abstract
Abstract Trabecular bone anisotropy, describing preferential trabecular co‐alignment, is a proxy for its long‐term loading history. Trabecular anisotropy varies locally, thus rendering averaged calculations across an entire bone inutile. Here we present a 3D trabecular anisotropy mapping method using vector fields where each vector reflects the extent of local co‐alignment of the elementary units of surface. 3D anisotropy maps of hundreds of thousands of vectors were visualized by their magnitude and direction. Similarly, volume fraction was mapped as 3D scalar fields. We constructed anisotropy and volume fraction maps using micro‐computed tomography of four presumably nonpathologic human calcanei and compared their anisotropy signature with pathologically loaded calcanei in club foot and calcaneonavicular ankylosis. In the nonpathologic calcaneus, a pattern of four anisotropy trajectories (bands) was consistently identified as dorsal, plantar, Achilles', and peroneal bands. Both pathologic specimens deviated from the nonpathologic maps. The calcaneus in the congenitally disused club foot showed very low local anisotropy values, no co‐oriented bands, and low volume fraction. The ankylosed calcaneus showed lower anisotropy than the nonpathologic calcaneus, but not to the same extent as the club foot, and showed patchy high volume fraction. The directionality of co‐oriented bands was barely discernable in the ankylosed calcaneus as compared to nonpathologic calcaneus. The anisotropy signature of the nonpathologic calcaneus is consistent with a kinetic loading pattern attributable to walking. The loss of this kinetic loading results in an absent/vanishing anisotropy signature. Such 3D mapping adds new dimensions to quantitative bioimaging of bone and the understanding of skeletal adaptation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".