Computerized Quantification of Joint Space Narrowing and Periarticular Demineralization in Patients With Rheumatoid Arthritis Based on Digital X-Ray Radiogrammetry
Bibliographic record
Abstract
OBJECTIVES: The aim of our work was to evaluate digital x-ray radiogrammetry (DXR) for the quantification of disease-related periarticular demineralization and computerized analysis of joint space distances (JSDA) for the measurement of joint space narrowing as a new diagnostic method for the early detection of joint-associated alterations and for monitoring disease progression in patients with rheumatoid arthritis (RA). MATERIALS AND METHODS: Digital radiographs in 313 patients with varying severity of RA were performed annually and assessed by 2 radiologists using modified Larsen and also the Sharp scores within an observation period of 3 years. The hand radiographs underwent measurements of bone mineral density (BMD) and metacarpal index (MCI) by DXR, as well as computerized JSDA at the metacarpal-phalangeal articulation (JSD-MCP) for a cross-sectional and longitudinal study design. RESULTS: Both DXR-BMD (-29.6%; P < 0.01) and DXR-MCI (-31.0%; P < 0.01) revealed a notable reduction dependent on the severity of RA (from grade 1 to grade 5 of the modified Larsen score); the severity dependent decrease of mean JSD-MCP ranged from -31.9% (P < 0.01; Sharp erosion part) to -39.1% (P < 0.01) for the modified Larsen score. Over an observation period of 3 years, a significant decrease of DXR-BMD (-22.3%) and DXR-MCI (-23.3%) as well as JSD-MCP mean (-17.5%) was observed (P < 0.05), whereas an accentuated decline of DXR and JSDA parameters was verified for patients without disease-modifying antirheumatic drugs or methotrexate therapy. CONCLUSION: Computerized analysis of hand radiographs by DXR and JSDA is a promising approach to assess the severity and to monitor the progression of RA because DXR and JSDA are timely able to measure periarticular demineralization and also narrowing of JSD-MCP dependent on the severity, the medical treatment and the course of RA.
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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".