CT-based internal density calibration for opportunistic skeletal assessment using abdominal CT scans
Why this work is in the frame
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Bibliographic record
Abstract
CT-based opportunistic skeletal assessment complements current osteoporosis diagnosis. Quantitative assessment by internal density calibration overcomes the limitations of phantom-based calibration. We sought to establish and validate an internal calibration technique using abdominal CT scans and establish reproducibility precision for three density calibration techniques. Ten full-body cadavers were CT scanned at the spine and pelvis with a calibration phantom. Internal calibration was performed using in-scan tissue references and deriving a voxel-specific calibration. Bone mineral density (BMD) and finite element (FE) failure load assessed skeletal health. Three independent users measured intra-exam precision by manual tissue selection. To verify results, ten subjects were imaged using an abdominal imaging protocol. Internal calibration performed equivalently to gold-standard phantom-based calibration in the cadaver spine and hip. Internal calibration BMD precision in the spine was 7 mg/cc (4.9%) and FE precision was 163 N (7.2%), whereas phantom-based precision was 3 mg/cc (1.8%) and 77 N (3.8%). Internal calibration hip BMD and FE precision was 11 mg/cc (5.3%) and 84 N (6.0%), whereas phantom-based precision was 2 mg/cc (1.3%) and 30 N (3.4%). Using the abdominal imaging protocol, internal calibration performed comparably to phantom-based calibration. Internal calibration provides BMD and FE outcome precision within 7.2% for opportunistic skeletal health assessment.
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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 | 0.001 |
| 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 it