Erosions Are the Most Relevant Magnetic Resonance Imaging Features in Quantification of Sacroiliac Joints in Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: To determine the most relevant radiological features in quantitative magnetic resonance imaging (MRI) of sacroiliac (SI) joints in patients with recent-onset ankylosing spondylitis (AS) versus patients with SI involvement due to other rheumatic diseases, or to degenerative SI pain. METHODS: We retrospectively analyzed laboratory values, clinical data, and MRI of the SI joints of 179 patients admitted for evaluation of AS-suspicious SI pain. Standardized MRI sequences were performed at time of first presentation, then archived, and retrospectively quantitatively assessed using a modified SPARCC method for formal statistical comparisons. RESULTS: Of all patients, 27 (15%) were diagnosed with definite AS. The remainder had SI involvement in other rheumatic diseases, HLA-B27- spondyloarthropathy, or nonspecific degenerative changes. While joint space irregularities, bone marrow edema, subcortical cysts, and contrast medium enhancement were found in MRI of all patients, these features were inconsistent, and only erosions were statistically significantly (p < 0.02) in patients diagnosed with AS. Only in AS, the presence of erosions and the quantitative SPARCC erosion subscore correlated to a statistically significant degree (p < 0.02) with laboratory levels of inflammation. CONCLUSION: Erosions alone, not bone marrow edema or contrast medium enhancement, are the most disease-specific measurable imaging findings in SI MRI of patients with AS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".