Reproducible metacarpal joint space width measurements using 3D analysis of images acquired with high-resolution peripheral quantitative computed tomography
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Bibliographic record
Abstract
OBJECTIVE: Joint space narrowing is an important feature of progressive joint damage and functional impairment in rheumatoid arthritis (RA). Methods to provide a continuous measurement of joint space width have not been adopted in research or clinical settings. High-resolution peripheral quantitative computed tomography (HR-pQCT) (Scanco Medical AG, Brüttisellen, Switzerland) accurately and reproducibly images bone microstructure at a nominal isotropic voxel dimension of 82 μm. Given the ability of HR-pQCT to detect bone margins with high precision, we developed methodology to measure a three-dimensional (3D) metacarpophalangeal (MCP) joint space width and tested the reproducibility of the scan protocol with hand repositioning. MATERIALS AND METHODS: Consecutive HR-pQCT scans of the 2nd and 3rd MCP joints of ten subjects with early RA (70% female, mean age 45 years), with repositioning between scans, were obtained. The periosteal edges of the metacarpal head and proximal phalanx base were detected using the μCT Evaluation Program V6.0 (Scanco Medical AG). Using the method of 'fitting maximal spheres', the joint space width and distribution of joint space thickness was estimated. RESULTS: The mean minimum joint space width of the 2nd MCP was 1.82 mm (SD 0.20) and of the 3rd MCP 1.84 mm (SD 0.23). Reproducibility with repositioning was reliable, with overlapping filtered histograms and a root square mean coefficient of variance of 4.8%. CONCLUSIONS: We provide reproducible methodology for evaluating the joint space width of the MCP joints. When combined with the assessment of erosions and periarticular bone density, HR-pQCT may be the ideal technology to assess disease activity and progression in RA.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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