Development and Validation of a Magnetic Resonance Imaging Reference Criterion for Defining a Positive Sacroiliac Joint Magnetic Resonance Imaging Finding in Spondyloarthritis
Bibliographic record
Abstract
OBJECTIVE: To validate a magnetic resonance imaging (MRI) reference criterion for a positive sacroiliac (SI) joint MRI finding based on the level of confidence in the classification of spondyloarthritis (SpA) by expert MRI readers. METHODS: Four readers assessed SI joint MRIs in 2 inception cohorts (cohorts A and B) of 157 consecutive patients with back pain ages ≤50 years and 20 age-matched healthy controls. Patients were classified according to clinical examination and pelvic radiography as having nonradiographic axial SpA (n = 51), ankylosing spondylitis (n = 34), or nonspecific back pain (n = 72). Readers indicated their level of confidence in their classification of SpA on a 0-10 scale, where 0 = definitely not SpA and 10 = definite SpA. The MRI reference criterion was prespecified by consensus as the majority of readers indicating a confidence score of 8-10; the absence of SpA required all readers to indicate non-SpA (a confidence score of 0-4). We calculated interreader reliability and agreement between MRI-based and clinical classification using kappa statistics. We estimated cutoff values for MRI lesions attaining a specificity of ≥0.90 for SpA. RESULTS: In cohorts A and B, 76.4% and 71.6% of subjects met the MRI criterion, respectively. The kappa values for interreader agreement were 0.76 for cohort A and 0.80 for cohort B and between MRI-based and clinical assessment were 0.93 for cohort A and 0.57 for cohort B. Using this MRI reference criterion, the cutoff for the number of affected SI joint quadrants needed to reach a predefined specificity of ≥0.90 was ≥2 for bone marrow edema (BME) in both cohorts and ≥1 for erosion in both cohorts, and the BME and/or erosion lesions increased sensitivity without reducing specificity. CONCLUSION: This data-driven study using 2 inception cohorts and comparing clinical and MRI-based classification supports the case for including both erosion and BME to define a positive SI joint MRI finding for the classification of axial SpA.
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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 | 0.013 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".