Systematic review with meta‐analysis: magnetic resonance enterography signs for the detection of inflammation and intestinal damage in Crohn's disease
Bibliographic record
Abstract
BACKGROUND: In the treatment of Crohn's disease (CD), mucosal healing has become a major goal, with the hope of avoiding intestinal damage from chronic inflammation. Magnetic resonance enterography (MRE) has emerged as a non-invasive means of monitoring inflammation and damage. AIMS: As part of the development of MRE-based multi-item measures of inflammation and damage for paediatric studies, we carried out a systematic review and meta-analysis to identify MRE variables used to describe these two distinct concepts. METHODS: 2501 studies of MRI and CD were identified. Studies written in any language reporting individual MRE signs for patients diagnosed with CD were included. Two-hundred-and-forty-four studies were fully reviewed and 62 were included (inflammation, n = 51; damage, n = 24). Sensitivity, specificity and associated confidence intervals were calculated, and hierarchical summary ROC curves were constructed for each MRE sign. RESULTS: A total of 22 MRE signs were used to reflect inflammation, and 9 to reflect damage. Diagnostic accuracy of MRE signs of inflammation and damage was heterogeneous; however, wall enhancement, mucosal lesions and wall T2 hyperintensity were the most consistently useful for inflammation (most sensitivities >80% and specificities >90%), and detection of abscess and fistula were most consistently useful for damage (most sensitivities >90%, specificities >95%). CONCLUSIONS: Identifying the best MRE variables to reflect inflammation and damage will maximise the utility of this rapidly emerging technique and is the first stage of constructing MRE-based indices for evaluating inflammation and intestinal damage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".