Abstract
Fibrosis is a pathological process that occurs due to chronic inflammation, leading to the proliferation of fibroblasts and the excessive deposition of extracellular matrix (ECM). The process of long-term fibrosis initiates with tissue hypofunction and progressively culminates in the ultimate manifestation of organ failure. Intestinal fibrosis is a significant complication of Crohn’s disease (CD) that can result in persistent luminal narrowing and strictures, which are difficult to reverse. In recent years, there have been significant advances in our understanding of the cellular and molecular mechanisms underlying intestinal fibrosis in inflammatory bowel disease (IBD). Significant progress has been achieved in the fields of pathogenesis, diagnosis, and management of intestinal fibrosis in the last few years. A significant amount of research has also been conducted in the field of biomarkers for the prediction or detection of intestinal fibrosis, including novel cross-sectional imaging modalities such as positron emission tomography (PET) and single photon emission computed tomography (SPECT). Molecular imaging represents a promising biomedical approach that enables the non-invasive visualization of cellular and subcellular processes. Molecular imaging has the potential to be employed for early detection, disease staging, and prognostication in addition to assessing disease activity and treatment response in IBD. Molecular imaging methods also have a potential role to enabling minimally invasive assessment of intestinal fibrosis. This review discusses the role of molecular imaging in combination of AI in detecting CD fibrosis.
Acknowledgments
The authors extend their appreciation to the Deputyship for Research& Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number ISP23-100.The authors would also like to thank Jazan university, Saudi Arabia, for using the online facilities to complete this research.
Ethical approval
This review did not require ethical approval as it was based on previously published studies.
Authors contributions
Conceptualization: Ali S. Alyami, Wael A. Ageeli, Yahia Madkhali
Data curation: Ali S. Alyami, Yahia Madkhali
Investigation: Ali S. Alyami, Naif A. Majrashi
Writing – original draft: Ali S. Alyami, Naif A Majrashi, Yahia Madkhali,
Writing – review & editing: Naif A Majrashi, Wael A. Ageeli, Yahia Madkhali, Turkey Refaee, Bandar Alwadani, Meaad Elbashir, Sarra Ali, Heham El-Bahkiry and Abdullah Althobity.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study are available from the corresponding author, [Dr Alyami], upon reasonable request.