Comparison of magnetic resonance enterography and video capsule endoscopy in evaluating small bowel disease
Bibliographic record
Abstract
PURPOSE: The goal of this study was to compare magnetic resonance enterography (MRE) and video capsule endoscopy (VCE) in suspected small bowel disease. MATERIALS AND METHODS: Nineteen patients with suspected small bowel disease participated in a prospective clinical comparison of MRE versus VCE. Both methods were evaluated separately and in conjunction with respect to a combined diagnostic endpoint based on clinical, laboratory, surgical, and histopathological findings. The Fisher's exact and j tests were used in comparing MRE and VCE. RESULTS: Small bowel pathologies were found in 15 out of 19 patients: Crohn's disease (n= 5), lymphoma (n= 4), lymphangioma (n= 1), adenocarcinoma (n= 1), postradiation enteropathy (n= 1), NSAID-induced enteropathy (n =1), angiodysplasia (n= 1), and small bowel adhesions (n= 1). VCE and MRE separately and in conjunction showed sensitivities of 92.9, 71.4, and 100% and specificities of 80, 60, and 80% (kappa= 0.73 vs. kappa = 0.29; P= 0.31/kappa = 0.85), respectively. In four patients, VCE depicted mucosal pathologies missed by MRE. MRE revealed 19 extraenteric findings in 11 patients as well as small bowel adhesions not detected on VCE (n= 1). CONCLUSION: VCE can readily depict and characterize subtle mucosal lesions missed at MRE, whereas MRE yields additional mural, perienteric, and extraenteric information. Thus, VCE and MRE appear to be complementary methods which, when used in conjunction, may better characterize suspected small bowel disease.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".