Erosions and Fatty Lesions of Sacroiliac Joints in Patients with Axial Spondyloarthritis: Evaluation of Different MRI Techniques and Two Scoring Methods
Bibliographic record
Abstract
OBJECTIVE: Assessment of structural damage of sacroiliac joints (SIJ) in patients with axial spondyloarthritides (axSpA) has been discussed as a useful outcome measure in clinical trials. The aim of our study was to evaluate different magnetic resonance imaging (MRI) scoring methods and pulse sequences with a focus on fatty lesions and bony erosions. METHODS: Seventy-five patients with the diagnosis of axSpA underwent MRI at 3 timepoints as part of the ESTHER trial, which compared 2 groups of patients treated with etanercept or sulfasalazine. Two MRI sequences [unenhanced T1-weighted (T1w) turbo spin-echo (TSE) and unenhanced T1w opposed-phase gradient-echo sequences (opGRE)] and 2 different scoring systems (simple and comprehensive Berlin method) were used for the evaluation of fatty lesions and erosions of the SIJ. Differences between techniques and methods were evaluated by intraclass correlation coefficients (ICC) and standardized response means (SRM). RESULTS: Applying the simple Berlin method, mean fatty lesion scores for etanercept-treated patients were 4.59 and 5.19 at baseline and Week 48, respectively, while the comprehensive Berlin method revealed mean fatty lesion scores of 6.59 and 7.64, respectively. Corresponding SRM were 0.59 and 0.86 for simple and comprehensive methods, respectively, while ICC dropped from 0.76-0.77 to 0.59-0.62. Scoring of erosions on T1w opGRE images resulted in a higher interreader agreement (ICC of 0.65) compared to T1w TSE sequences (ICC of 0.18). CONCLUSION: Better characterization of fatty lesion changes within 1 year was achieved by the comprehensive Berlin scoring method; however, more reader variation has to be taken into account. The delineation of erosions is markedly improved when using T1w opGRE pulse sequences.
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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 | 0.003 | 0.005 |
| 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 | 0.000 |
| 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 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".