Protocol development for synchrotron contrast-enhanced CT of human hip cartilage
Bibliographic record
Abstract
Understanding hip osteoarthritis requires new investigational tools for quantitative studies of biophysical and biomechanical properties as well as for determination of structure. Three new protocols to study pathological changes in cartilage and to measure cartilage thickness in intact human hips are described using synchrotron contrast enhanced computed tomography (sCECT) with the iodinated contrast agent CA4+. Ten human cadaver hips were prepared and injected with CA4+ using three different methods, all of which included rotation and distraction of the joint. CA4+ diffusion into cartilage was monitored using sCECT. The thickness of acetabular and femoral cartilage was also measured. Diffusion times ranged from 2 h to 75 h, depending on the injection protocol and the cartilage region. Direct single injection of the contrast through the labrum resulted in the fastest diffusion times. The iodine attenuation coefficient, which reflects the contrast agent distribution in the cartilage, ranged from 0.0142/cm to 0.1457/cm. Three injections at the head/neck conjunction area yielded the highest iodine attenuation coefficients in cartilage. The femoral cartilage in the Superior-Medial compartment was significantly thicker than in the other 3 femoral compartments, and femoral cartilage in the Superior-Anterior compartment was significantly thinner than the other 3 femoral compartments. The acetabular cartilage in the Superior compartment was significantly thicker than that in the Superior-Posterior compartment. sCECT with CA4+ allows assessment of hip cartilage thickness with 0.1 mm isotropic voxel size, sufficient for evaluating cartilage pathology and biomechanics.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".