Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges

Inflammatory bowel disease (IBD), encompassing Crohn's disease and ulcerative colitis, remains a chronic management challenge despite the success of biological therapies such as infliximab. A major limitation is secondary loss of response, which affects a substantial proportion of patients and complicates long-term treatment strategies. Emerging technologies such as radiomics, which converts medical images into quantitative features, and artificial intelligence (AI), which integrates complex multimodal data, offer new opportunities to predict treatment response, monitor disease activity, and personalize therapy. By combining imaging-derived radiomic features with clinical and laboratory information, AI-driven models can provide early, actionable insights to guide therapeutic decisions. This editorial discusses the promise and limitations of these approaches, emphasizing how they can be integrated into clinical decision-making pathways. While challenges in standardization, validation, and clinician adoption remain, radiomics and AI represent important steps toward precision medicine, with the potential to improve outcomes and optimize care for patients with IBD.

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Publication Details

Journal
World Journal of Gastroenterology
Published
2025-11-13
DOI
https://doi.org/10.3748/wjg.v31.i42.112107
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges

Shanshan Xie, Zhigang Liu
1 citations
World Journal of Gastroenterology
Radiomics and Machine Learning in Medical Imaging
1.36
article

Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges

Shanshan Xie, Zhigang Liu
article en
1 citations

Abstract

Inflammatory bowel disease (IBD), encompassing Crohn's disease and ulcerative colitis, remains a chronic management challenge despite the success of biological therapies such as infliximab. A major limitation is secondary loss of response, which affects a substantial proportion of patients and complicates long-term treatment strategies. Emerging technologies such as radiomics, which converts medical images into quantitative features, and artificial intelligence (AI), which integrates complex multimodal data, offer new opportunities to predict treatment response, monitor disease activity, and personalize therapy. By combining imaging-derived radiomic features with clinical and laboratory information, AI-driven models can provide early, actionable insights to guide therapeutic decisions. This editorial discusses the promise and limitations of these approaches, emphasizing how they can be integrated into clinical decision-making pathways. While challenges in standardization, validation, and clinician adoption remain, radiomics and AI represent important steps toward precision medicine, with the potential to improve outcomes and optimize care for patients with IBD.

World Journal of GastroenterologyVol. 31(42)
Imperial College London (GB)
Openalex Percentile: Top 14%
Radiomics and Machine Learning in Medical Imaging
1.36
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Expanding the role of radiomics and artificial intelligence in the management of inflammatory bowel disease: Insights, opportunities, and challenges — Shanshan Xie, Zhigang Liu · World Journal of Gastroenterology (2025) | TGRS Research Map | TGRS