The EXTENT Study: Results From an International Expert Delphi Consensus to Define Ultrasonographic Parameters for Measuring Bowel Damage in Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND & AIMS: A primary aim in managing Crohn's disease (CD) is preventing bowel damage. The Lémann index (LI) quantifies structural bowel damage using magnetic resonance enterography (MRE) or computed tomography enterography (CTE) and, for colonic CD, colonoscopy. Intestinal ultrasonography (IUS) provides a noninvasive imaging alternative, although its role in LI assessment remains unexplored. This study aimed to establish a consensus on parameters and acquisition protocol for scoring small bowel and colonic damage using IUS in evaluating the LI. METHODS: Thirty international experts in IUS and/or MRE participated in a 3-round Delphi process. Participants provided feedback and rated statements on IUS parameters and acquisition protocol in 2 online rounds. During the final in-person round, unresolved items were discussed and voted upon. Statements with at least 80% agreement were accepted. RESULTS: Twenty-two statements reached a consensus: 10 defined IUS parameters for stricturing and penetrating lesions for scoring LI-IUS, and 12 addressed optimal IUS cineloop acquisition for centralized review. No consensus on IUS equivalents for grade 1 stricturing lesions in the small bowel and colon was reached. CONCLUSIONS: Ultrasonographic equivalents for assessing small bowel and colonic damage in CD were derived to align with the validated LI criteria for MRE and colonoscopy. These statements mark the first phase of the EXTENT project, supporting the potential use of IUS in clinical practice and disease modification trials as an alternative tool for bowel damage assessment. The lack of consensus on grade 1 stricturing lesions suggests further exploration of IUS parameters is required.
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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 | 0.191 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".