ECCO-ESGAR Topical Review on Optimizing Reporting for Cross-Sectional Imaging in Inflammatory Bowel Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND AIMS: The diagnosis and follow up of patients with inflammatory bowel disease [IBD] requires cross-sectional imaging modalities, such as intestinal ultrasound [IUS], magnetic resonance imaging [MRI] and computed tomography [CT]. The quality and homogeneity of medical reporting are crucial to ensure effective communication between specialists and to improve patient care. The current topical review addresses optimized reporting requirements for cross-sectional imaging in IBD. METHODS: An expert consensus panel consisting of gastroenterologists, radiologists and surgeons convened by the ECCO in collaboration with ESGAR performed a systematic literature review covering the reporting aspects of MRI, CT, IUS, endoanal ultrasonography and transperineal ultrasonography in IBD. Practice position statements were developed utilizing a Delphi methodology incorporating two consecutive rounds. Current practice positions were set when ≥80% of the participants agreed on a recommendation. RESULTS: Twenty-five practice positions were developed, establishing standard terminology for optimal reporting in cross-sectional imaging. Assessment of inflammation, complications and imaging of perianal CD are outlined. The minimum requirements of a standardized report, including a list of essential reporting items, have been defined. CONCLUSIONS: This topical review offers practice recommendations to optimize and homogenize reporting in cross-sectional imaging in IBD.
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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 | 0.001 |
| 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 it