Assessment of Crohn’s disease-associated small bowel strictures and fibrosis on cross-sectional imaging: a systematic review
Bibliographic record
Abstract
Patients with Crohn's disease commonly develop ileal and less commonly colonic strictures, containing various degrees of inflammation and fibrosis. While predominantly inflammatory strictures may benefit from a medical anti-inflammatory treatment, predominantly fibrotic strictures currently require endoscopic balloon dilation or surgery. Therefore, differentiation of the main components of a stricturing lesion is key for defining the therapeutic management. The role of endoscopy to diagnose the nature of strictures is limited by the superficial inspection of the intestinal mucosa, the lack of depth of mucosal biopsies and by the risk of sampling error due to a heterogeneous distribution of inflammation and fibrosis within a stricturing lesion. These limitations may be in part overcome by cross-sectional imaging techniques such as ultrasound, CT and MRI, allowing for a full thickness evaluation of the bowel wall and associated abnormalities. This systematic literature review provides a comprehensive summary of currently used radiologic definitions of strictures. It discusses, by assessing only manuscripts with histopathology as a gold standard, the accuracy for diagnosis of the respective modalities as well as their capability to characterise strictures in terms of inflammation and fibrosis. Definitions for strictures on cross-sectional imaging are heterogeneous; however, accuracy for stricture diagnosis is very high. Although conventional cross-sectional imaging techniques have been reported to distinguish inflammation from fibrosis and grade their severity, they are not sufficiently accurate for use in routine clinical practice. Finally, we present recent consensus recommendations and highlight experimental techniques that may overcome the limitations of current technologies.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".