Magnetic resonance imaging for suspected perianal Crohn's disease in children: a multi-reader agreement study
Bibliographic record
Abstract
OBJECTIVES: We aimed to assess inter-radiologist agreement when interpreting pelvic MRI in children with newly diagnosed perianal Crohn's disease (CD). MATERIALS AND METHODS: In this retrospective multi-reader study, we identified pediatric patients (< 18 years of age) who underwent a pelvic MRI examination for newly diagnosed perianal CD. Images were de-identified and uploaded to a cloud-based image platform for review by 13 fellowship-trained pediatric radiologists The reviewers assessed for the presence of a fistula and abscess, categorization of different imaging findings, and classification using the Parks and St James' University Hospital systems. Fleiss' kappa (κ) statistics and intra-class correlation coefficients (ICC) were used to measure inter-reader agreement, along with 95% confidence intervals (CI). RESULTS: Forty-six patients were included in our study (median age = 13.0 years [IQR: 10.5 to 16.0 years]); thirty-five (76.1%) were boys. Most imaging features showed fair agreement (κ = 0.21 to 0.35). There was moderate agreement for categorical fistula length (κ = 0.42 [95% CI: 0.32 to 0.53]), involvement of the genitalia (κ = 0.45 [95% CI: 0.26 to 0.63]), and presence of an abscess/collection (κ = 0.52 [95% CI: 0.31 to 0.73]). Maximum abscess/collection length had good agreement (ICC = 0.81 [95% CI: 0.41, 1.00]). There was an almost equal split (yes vs. no: 50.7% vs. 49.3%) regarding whether postcontrast T1-weighted images added value compared to T2-weighted images alone across all radiologists and examinations. CONCLUSION: Inter-radiologist agreement when interpreting pelvic MRI for perianal CD in children is fair for most imaging features, with fewer features demonstrating moderate or good agreement. KEY POINTS: Question Pelvic magnetic resonance imaging (MRI) is used for diagnosing and monitoring children with perianal Crohn's disease (CD). Limited information is known about inter-radiologist agreement. Findings Agreement between pediatric radiologists when interpreting MRI for perianal CD in children is only fair for most imaging features (κ = 0.21 to 0.35). Clinical relevance Understanding MRI inter-radiologist agreement is crucial to improve the reliability of pelvic MRI in children with perianal Crohn's disease since it may affect patient management (e.g., surgery); further radiologist education and improved imaging feature definitions may help improve inter-radiologist agreement.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".