Multiparametric Magnetic Resonance Imaging, Autoimmune Hepatitis, and Prediction of Disease Activity
Bibliographic record
Abstract
Noninvasive monitoring of disease activity in autoimmune hepatitis (AIH) has potential advantages for patients for whom liver biopsy is invasive and with risk. We sought to understand the association of multiparametric magnetic resonance imaging (mpMRI) with clinical course of patients with AIH. We prospectively recruited 62 patients (median age, 55 years; 82% women) with clinically confirmed AIH. At recruitment, patients underwent mpMRI with Liver MultiScan alongside clinical investigations, which were repeated after 12‐18 months. Associations between iron‐corrected T1 (cT1) and other markers of disease were investigated at baseline and at follow‐up. Discriminative performance of cT1, liver stiffness, and enhanced liver fibrosis (ELF) to identify those who failed to maintain remission over follow‐up was investigated using the areas under the receiver operating characteristic curves (AUCs). Baseline cT1 correlated with alanine aminotransferase (Spearman’s correlation coefficient [ r S ] = 0.28, P = 0.028), aspartate aminotransferase ( r S = 0.26, P = 0.038), international normalized ratio ( r S = 0.35 P = 0.005), Model for End‐Stage Liver Disease ( r S = 0.32, P = 0.020), ELF ( r S = 0.29, P = 0.022), and liver stiffness r S = 0.51, P < 0.001). After excluding those not in remission at baseline (n = 12), 32% of the remainder failed to maintain remission during follow‐up. Failure to maintain remission was associated with significant increases in cT1 over follow‐up (AUC, 0.71; 95% confidence interval [CI], 0.52‐0.90; P = 0.035) but not with changes in liver stiffness (AUC, 0.68; 95% CI, 0.49‐0.87; P = 0.067) or ELF (AUC, 0.57; 95% CI, 0.37‐0.78; P = 0.502). cT1 measured at baseline was a significant predictor of future loss of biochemical remission (AUC, 0.68; 95% CI, 0.53‐0.83; P = 0.042); neither liver stiffness (AUC, 0.53; 95% CI, 0.34‐0.71; P = 0.749) nor ELF (AUC, 0.52; 95% CI, 0.33‐0.70; P = 0.843) were significant predictors of loss of biochemical remission. Conclusion: Noninvasive mpMRI has potential to contribute to risk stratification in patients with AIH.
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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".