Diffusion-weighted imaging is a sensitive biomarker of response to biologic therapy in enthesitis-related arthritis
Bibliographic record
Abstract
Objective: The aim was to evaluate diffusion-weighted imaging (DWI) as a tool for measuring treatment response in adolescents with enthesitis-related arthropathy (ERA). Methods: Twenty-two adolescents with ERA underwent routine MRI and DWI before and after TNF inhibitor therapy. Each patient's images were visually scored by two radiologists using the Spondyloarthritis Research Consortium of Canada system, and sacroiliac joint apparent diffusion coefficient (ADC) and normalized ADC (nADC) were measured for each patient. Therapeutic clinical response was defined as an improvement of ⩾ 30% physician global assessment and radiological response defined as ⩾ 2.5-point reduction in Spondyloarthritis Research Consortium of Canada score. We compared ADC and nADC changes in responders and non-responders using the Mann-Whitney-Wilcoxon test. Results: For both radiological and clinical definitions of response, reductions in ADC and nADC after treatment were greater in responders than in non-responders (for radiological response: ADC: P < 0.01; nADC: P = 0.055; for clinical response: ADC: P = 0.33; nADC: P = 0.089). ADC and nADC could predict radiological response with a high level of sensitivity and specificity and were moderately sensitive and specific predictors of clinical response (the area under the receiver operating characteristic curves were as follows: ADC: 0.97, nADC: 0.82 for radiological response; and ADC: 0.67, nADC: 0.78 for clinical response). Conclusion: DWI measurements reflect the response to TNF inhibitor treatment in ERA patients with sacroiliitis as defined using radiological criteria and may also reflect clinical response. DWI is more objective than visual scoring and has the potential to be automated. ADC/nADC could be used as biomarkers of sacroiliitis in the clinic and in clinical trials.
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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 | 0.000 |
| 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 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".