ArticleJournal of Crohn's & colitis2024
Radiomics to Detect Inflammation and Fibrosis on Magnetic Resonance Enterography in Stricturing Crohn's Disease.
Article in Journal of Crohn's & colitis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The global academic distribution and changes in research hotspots of artificial intelligence in inflammatory bowel disease since 2000.Frontiers in medicine · 2025Pooled it
- Artificial intelligence in inflammatory bowel disease: From current evidence, clinical translation, and the road to precision medicine.Chinese medical journal · 2026Review
- Development of a Computed Tomography Enterography-Based Radiomics Model to Characterize Inflammation, Fibrosis, and Smooth Muscle Thickening in Stricturing Crohn's Disease.The American journal of gastroenterology · 2026Article
- Review
- Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging.Npj imaging · 2026Article
- Crohn's disease: research progress in decoding pathogenic multi-network and precision management of artificial intelligence radiomics.Frontiers in immunology · 2026Review
- Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges.World journal of gastroenterology · 2025Article
- Imaging monitoring contributes to the "treat-to-target" strategy in the management of Crohn's disease.World journal of gastroenterology · 2025Article
- Beyond Fixed Thresholds: Cluster-Derived MRI Boundaries Improve Assessment of Crohn's Disease Activity.Journal of clinical medicine · 2025Article
- The Role of Imaging in Inflammatory Bowel Diseases: From Diagnosis to Individualized Therapy.Diagnostics (Basel, Switzerland) · 2025Review
- Quantifying "Medical Renal Disease": A Pediatric Pilot Study Using Ultrasound Radiomics for Differentiating Acute Kidney Injury and Chronic Kidney Disease.Diagnostics (Basel, Switzerland) · 2025Article
- Development and validation of a CT-based radiomic nomogram for predicting surgical resection risk in patients with adhesive small bowel obstruction.BMC medical imaging · 2025Article
- Intestinal strictures in Crohn's disease: An update from 2023.United European gastroenterology journal · 2024Review
- How to Evaluate Fibrosis in IBD?Diagnostics (Basel, Switzerland) · 2023Review
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Authors and funding
11 authors.
Funding
Abstract
BACKGROUND AND
aimsNon-invasive cross-sectional imaging via magnetic resonance enterography [MRE] offers excellent accuracy for the diagnosis of stricturing complications in Crohn's disease [CD] but is limited in determining the degrees of fibrosis and inflammation within a stricture. We developed and validated a radiomics-based machine-learning model for separately characterizing the degree of histopathological inflammation and fibrosis in CD strictures and compared it to centrally read visual radiologist scoring of MRE.
methodsThis single-centre, cross-sectional study included 51 CD patients [n = 34 for discovery; n = 17 for validation] with terminal ileal strictures confirmed on diagnostic MRE within 15 weeks of resection. Histopathological specimens were scored for inflammation and fibrosis and spatially linked with corresponding pre-surgical MRE sequences. Annotated stricture regions on MRE were scored visually by radiologists as well as underwent 3D radiomics-based machine learning analysis; both were evaluated against histopathology.
resultsTwo distinct sets of radiomic features capturing textural heterogeneity within strictures were linked with each of severe inflammation or severe fibrosis across both the discovery (area under the curve [AUC = 0.69, 0.83] and validation [AUC = 0.67, 0.78] cohorts. Radiologist visual scoring had an AUC = 0.67 for identifying severe inflammation and AUC = 0.35 for severe fibrosis. Use of combined radiomics and radiologist scoring robustly augmented identification of severe inflammation [AUC = 0.79] and modestly improved assessment of severe fibrosis [AUC = 0.79 for severe fibrosis] over individual approaches.
conclusionsRadiomic features of CD strictures on MRE can accurately identify severe histopathological inflammation and severe histopathological fibrosis, as well as augment performance of the radiologist visual scoring in stricture characterization.
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