The Chicago Mesenteric Fat Index: A Novel Metric for Point-of-Care Intestinal Ultrasound Evaluation of Mesenteric Fat Wrapping in Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND: Mesenteric fat (MF) wrapping is a characteristic feature of Crohn's disease (CD). Current assessment methods are limited to binary classification (presence/absence), restricting their utility in assessing disease progression and treatment response. This study aimed to develop and validate a novel semi-quantitative metric for grading MF wrapping using intestinal ultrasound (IUS), and to evaluate its reliability and clinical relevance. METHODS: This cross-sectional study included 95 ultrasound scans from 63 patients with CD. The novel index described here categorized MF wrapping into 3 categories: none, incomplete, and complete. Images were independently assessed to evaluate inter- and intrarater reliability. Associations between MF wrapping and clinical characteristics, inflammatory markers, and IUS parameters were analyzed. RESULTS: Interrater reliability for the MF index was moderate (κ = 0.452), while intrarater reliability was substantial (κ = 0.653), similar to binary assessment (κ = 0.572 and κ = 0.674 for inter- and intrarater reliability, respectively). MF wrapping was significantly associated with increased bowel wall thickness (OR, 6.74; P < .001), loss of bowel wall stratification (OR, 22.05; P < .001), hyperemia (OR, 8.09; P = .002), and presence of strictures (OR, 4.30; P = .002). Smoking status and lower serum albumin were significantly associated with increased MF wrapping. CONCLUSIONS: CMFI represents a proof-of-concept tool for semi-quantitative assessment of MF wrapping on IUS. While reproducible and associated with other disease markers, its incremental clinical utility remains to be established through prospective validation and longitudinal outcome studies.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".