Artificial intelligence: A new tool in the pathologist's armamentarium for the diagnosis of IBD.

Inflammatory bowel diseases (IBD) are classified into two entities, namely Crohn's disease (CD) and ulcerative colitis (UC), which differ in disease trajectories, genetics, epidemiological, clinical, endoscopic, and histopathological aspects. As no single golden standard modality for diagnosing IBD exists, the differential diagnosis among UC, CD, and non-IBD involves a multidisciplinary approach, considering professional groups that include gastroenterologists, endoscopists, radiologists, and pathologists. In this context, histological examination of endoscopic or surgical specimens plays a fundamental role. Nevertheless, in differentiating IBD from non-IBD colitis, the histopathological evaluation of the morphological lesions is limited by sampling and subjective human judgment, leading to potential diagnostic discrepancies. To overcome these limitations, artificial intelligence (AI) techniques are emerging to enable automated analysis of medical images with advantages in accuracy, precision, and speed of investigation, increasing interest in the histological analysis of gastrointestinal inflammation. This review aims to provide an overview of the most recent knowledge and advances in AI methods, summarizing its applications in the histopathological analysis of endoscopic biopsies from IBD patients, and discussing its strengths and limitations in daily clinical practice.

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© 2024 The Authors.

Déclaration de conflit d'intérêts

S Danese has served as a speaker, consultant, and advisory board member for Schering-Plough, AbbVie, Actelion, Alphawasserman, AstraZeneca, Cellerix, Cosmo Pharmaceuticals, Ferring, Genentech, Grunenthal, Johnson and Johnson, millennium Takeda, MSD, Nikkiso Europe GmbH, Novo Nordisk, Nycomed, Pfizer, Pharmacosmos, UCB Pharma and Vifor. The other authors have no relevant disclosures.