Quantitation of Circumferential Syndesmophyte Height along the Vertebral Rim in Ankylosing Spondylitis Using Computed Tomography
Bibliographic record
Abstract
OBJECTIVE: Using the 3-D imaging capability of computed tomography (CT), we developed an algorithm quantitating syndesmophyte height along the entire vertebral rim. We investigated its reliability and sensitivity to change, performed a 2-year longitudinal study, and compared it to CT measures of syndesmophyte volume. METHODS: We performed thoracolumbar spine CT scans on 33 patients at baseline, Year 1, and Year 2, and computed syndesmophyte height in 4 intervertebral disc spaces (IDS). Height was computed every 5° (72 angular sectors) along the vertebral rim. These 72 measures were summed to form the circumferential height per IDS, and results from 4 IDS were summed to provide results per patient. To assess reliability, we compared results between 2 scans performed on the same day in 9 patients. Validity was assessed by associations with spinal flexibility. RESULTS: Coefficient of variation for circumferential syndesmophyte height was 0.893% per patient, indicating excellent reliability. Based on the Bland-Altman analysis, an increase in circumferential height of more than 3.44% per patient represented a change greater than measurement error. At years 1 and 2, mean (SD) circumferential syndesmophyte height increases were 10.2% (11.7%) and 16.1% (14.0%), respectively. Sensitivity to change was 0.72 and 0.87 at years 1 and 2, respectively. Circumferential syndesmophyte height correlated with the Schober test (r = -0.56, p = 0.0003) and lateral thoracolumbar flexion (r = -0.73, p < 0.0001). CONCLUSION: CT-based circumferential syndesmophyte height had excellent reliability and good sensitivity to change. It was more highly correlated with spine flexibility than syndesmophyte volume. The algorithm shows promise for longitudinal studies of syndesmophyte growth.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".