Assessment of structural lesions in sacroiliac joints enhances diagnostic utility of magnetic resonance imaging in early spondylarthritis
Bibliographic record
Abstract
OBJECTIVE: To compare the diagnostic utility of T1-weighted and STIR magnetic resonance imaging (MRI) sequences in early spondylarthritis (SpA) using a standardized approach to the evaluation of sacroiliac (SI) joints, and to test whether systematic calibration of readers directed at recognition of abnormalities on T1-weighted MRI would enhance diagnostic utility. METHODS: Six readers independently assessed T1-weighted and STIR MRI scans of the SI joints from 187 subjects: 75 ankylosing spondylitis (AS) and 27 preradiographic inflammatory back pain (IBP) patients, and 26 mechanical back pain and 59 healthy volunteer controls ages ≤45 years. The exercise was repeated 6 months later on a random selection of 30 AS patients and 34 controls after calibration directed at lesions visible on T1-weighted MRI. Specific MRI lesions were recorded according to standardized definitions. In addition to deciding on the presence/absence of SpA, readers were asked which MRI sequence and which type of lesion was the primary basis for their diagnostic conclusion. RESULTS: Structural lesions were detected in 98% of AS patients and 64% of IBP patients. A diagnosis of SpA was based on T1-weighted or combined T1-weighted/STIR sequences in 82% of AS patients and 41% of IBP patients. Calibration enhanced the diagnostic utility of MRI in the majority of readers, especially those considered less experienced; the mean positive and negative likelihood ratios (of 6 readers) were 14.5 and 0.08 precalibration, respectively, and 22.2 and 0.02 postcalibration, respectively. CONCLUSION: Recognition of structural lesions on T1-weighted MRI contributes significantly to its diagnostic utility in early SpA. Rheumatologist training directed at detection of lesions visible on T1-weighted MRI enhances diagnostic utility.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".