ArticleWorld journal of gastroenterology2025
Longitudinal computed tomography-based delta-radiomics of visceral adipose tissue predicts infliximab secondary loss of response in Crohn's disease patients.
Article in World journal of gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Objective Endoscopic Assessment for Prediction of Secondary Loss of Response of Biologics in Crohn's Disease.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2026Article
- Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact.Nature reviews. Gastroenterology & hepatology · 2026Review
- Crohn's disease: research progress in decoding pathogenic multi-network and precision management of artificial intelligence radiomics.Frontiers in immunology · 2026Review
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6 authors.
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Abstract
backgroundVisceral adipose tissue (VAT) plays a role in the pathogenesis of Crohn's disease (CD) and is associated with treatment outcomes following infliximab (IFX) therapy. We developed and validated the first delta-radiomics model to quantify VAT heterogeneity as a predictive biomarker for IFX response in patients with CD.
aimTo develop a longitudinal computed tomography (CT)-based delta-radiomics model of VAT for predicting secondary loss of response (SLR) in patients with CD.
methodsThis retrospective study included 161 patients with CD who achieved clinical remission following IFX induction therapy between 2015 and 2023. All patients underwent CT enterography before IFX initiation and after completing induction therapy. VAT volume was delineated by two radiologists in consensus. Radiomics features were extracted from pre-treatment and post-induction CT images, and delta-radiomics features were calculated as follows: Delta features = Feature
resultsNine significant delta-radiomics features were used to develop the delta-radiomics model, yielding an area under the receiver operating characteristic curve (AUC) of 0.816 (95%CI: 0.737-0.896) in the training cohort and 0.750 (95%CI: 0.605-0.895) in the validation cohort. Multivariable logistic regression identified platelet count, Montreal behavior classification, and the VAT/subcutaneous adipose tissue volume ratio prior to treatment as independent risk factors for SLR. The combined model integrating clinical predictors and delta-radiomics features achieved superior predictive performance, with an AUC of 0.853 (95%CI: 0.786-0.921) in the training cohort and 0.812 (95%CI: 0.677-0.948) in the validation cohort.
conclusionWe developed a predictive model based on longitudinal changes in VAT, demonstrating significant potential for identifying patients with CD at high risk of SLR to IFX therapy.
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