ArticleFrontiers in medicine2025
Radiomics-based prediction of recurrent acute pancreatitis in individuals with metabolic syndrome using T2WI magnetic resonance imaging data.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Radiomics derived from MRI T2-weighted imaging combined with clinical variables for predicting disease severity in hypertriglyceridemic acute pancreatitis.Abdominal radiology (New York) · 2026Article
- A Metabolomics-Driven Integrated Machine Learning Framework for Early Prediction of Recurrent Acute Pancreatitis.Metabolites · 2026Article
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Authors and funding
5 authors.
Funding
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Abstract
Objective: This study sought to clarify the utility of T2-weighted imaging (T2WI)-based radiomics to predict the recurrence of acute pancreatitis (AP) in subjects with metabolic syndrome (MetS). Methods: Data from 196 patients with both AP and MetS from our hospital were retrospectively analyzed. These patients were separated into two groups according to their clinical follow-up outcomes, including those with first-onset AP ( Results: In the training set, the clinical, radiomics, and combined models yielded respective AUCs of 0.651, 0.825, and 0.883, with corresponding test sets of AUCs of 0.606, 0.776, and 0.878. Both the radiomics and combined models exhibited superior predictive effectiveness compared to the clinical model in both the training ( Conclusion: These findings highlight the superior predictive power of a T2WI-based radiomics model for predicting AP recurrence in patients with MetS, potentially supporting early interventions that can mitigate or alleviate RAP.
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