Site-matched assessment of structural and tissue properties of cortical bone using scanning acoustic microscopy and synchrotron radiation μCT
Bibliographic record
Abstract
200 MHz scanning acoustic microscopy (SAM) and synchrotron radiation muCT (SR-muCT) were used to assess microstructural parameters and tissue properties in site-matched regions of interest in cortical bone. Anterior and postero-lateral regions of ten cross sections from human cortical radius were explored. Structural parameters, including diameter and number of Haversian canals per cortical area (Ca.Dm, N.Ca/Ar) and porosity Po were assessed with both methods using a custom-developed image fusion and analysis software. Acoustic impedance Z and degree of mineralization of bone DMB were extracted separately for osteonal and interstitial tissues from the fused images. Structural parameter estimations obtained from radiographic and acoustic images were almost identical. DMB and impedance values were in the range between 0.77 and 1.28 g cm(-3) and 5.13 and 12.1 Mrayl, respectively. Interindividual and regional variations were observed, whereas the strongest difference was found between osteonal and interstitial tissues (Z: 7.2 +/- 1.1 Mrayl versus 9.3 +/- 1.0 Mrayl, DMB: 1.06 +/- 0.07 g cm(-3) versus 1.16 +/- 0.05 g cm(-3), paired t-test, p < 0.05). Weak, but significant correlations between DMB and Z were obtained for the osteonal (R(2) = 0.174, p < 10(-4)) and for the pooled (osteonal and interstitial) data. The regression of the pooled osteonal and interstitial tissue data follows a second-order polynomial (R(2) = 0.39, p < 10(-4)). Both modalities fulfil the requirement for a simultaneous evaluation of cortical bone microstructure and material properties at the tissue level. While SAM inspection is limited to the evaluation of carefully prepared sample surfaces, SR-muCT provides volumetric information on the tissue without substantial preparation requirements. However, SAM provides a quantitative estimate of elastic properties at the tissue level that cannot be captured by SR-muCT.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".