<i>In vivo</i> imaging of rat cortical bone porosity by synchrotron phase contrast micro computed tomography
Bibliographic record
Abstract
Cortical bone is a dynamic tissue which undergoes adaptive and pathological changes throughout life. Direct longitudinal tracking of this remodeling process holds great promise for improving our understanding of bone development, maintenance and senescence. The application of in vivo micro-computed tomography (micro-CT) has enabled longitudinal tracking of trabecular bone microarchitecture with commercially available scanners generally operating in the 10-20 µm voxel range with absorbed doses reported between 0.5 and 1 Gy. Imaging of cortical bone microarchitecture (porosity) requires higher resolution and thus in vivo imaging of these structures has not been achieved due to excessive radiation dose. In this study we tested the hypothesis that synchrotron propagation phase contrast micro-CT can enable in vivo imaging of cortical porosity in rats at doses comparable to those currently employed for trabecular bone imaging. Synchrotron imaging experiments were conducted at the Canadian Light Source using the bending magnet beamline of the BioMedical Imaging and Therapy (BMIT) facility. Protocol optimization (propagation distance, projection number) was conducted ex vivo on rat (Sprague-Dawley) forelimbs with dose determined by ion chamber and lithium fluoride crystal thermoluminescent dosimeters. Comparative ex vivo imaging was performed using laboratory in vivo scanning systems, identifying a range of doses between 1.2-3.6 Gy for common protocols. A final in vivo synchrotron protocol involving a 2.5 Gy dose was implemented with live rats. The resulting images demonstrated improved delineation of cortical porosity through the improved edge enhancement effect of phase contrast, opening the door to novel experimental studies involving the longitudinal tracking of remodeling.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".