Endoscopic imaging in inflammatory bowel disease: current developments and emerging strategies

Abstract

Introduction: Developments in enhanced and magnified endoscopy have signified major advances in endoscopic imaging of ileocolonic pathology in inflammatory bowel disease (IBD). Artificial intelligence is increasingly being used to augment the benefits of these advanced techniques. Nevertheless, treatment of IBD patients is frustrated by high rates of non-response to therapy, while delayed detection and failures to detect neoplastic lesions impede successful surveillance. A possible solution is offered by molecular imaging, which adds functional imaging data to mucosal morphology assessment through visualizing biological parameters. Other label-free modalities enable visualization beyond the mucosal surface without the need of tracers. Areas covered: A literature search up to May 2020 was conducted in PubMed/MEDLINE in order to find relevant articles that involve the (pre-)clinical application of high-definition white light endoscopy, chromoendoscopy, artificial intelligence, confocal laser endomicroscopy, endocytoscopy, molecular imaging, optical coherence tomography, and Raman spectroscopy in IBD. Expert opinion: Enhanced and magnified endoscopy have enabled an improved assessment of the ileocolonic mucosa. Implementing molecular imaging in endoscopy could overcome the remaining clinical challenges by giving practitioners a real-time in vivo view of targeted biomarkers. Label-free modalities could help optimize the endoscopic assessment of mucosal healing and dysplasia detection in IBD patients.

Standardization and implementation of fluorescence molecular endoscopy in the clinic

“… 16 , 21 Still, the success of AI implication will dependent on the amount of available and standardized data and the quality of the annotation of the data. 48 , 54 However, more data might be produced using the abovementioned anthropomorphic phantoms. 36 …”

“…6 If standardization is improved and clinical FME trials can be assessed objectively and compared, a next step would be the introduction of artificial intelligence (AI). 48 As the level of informational detail increases, the endoscopist is faced with increasingly complex information, resulting in a diagnostic challenge of real-time interpretation. AI methods are already commercially available in endoscopy, 49 and several computer-aided studies have been performed.…”

“…16,21 Still, the success of AI implication will dependent on the amount of available and standardized data and the quality of the annotation of the data. 48,54 However, more data might be produced using the abovementioned anthropomorphic phantoms. 36 In summary, the need for standardization in FME and the hurdles that still need to be overcome before a widespread clinical implementation of FME can be realized are described in this paper.…”

Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions

“…VCE includes pre-processing optical imaging techniques, such as Olympus' narrow-band imaging (NBI) and autofluorescence imaging, as well as the post-processing techniques Pentax's i-SCAN and Fujinon intelligent chromoendoscopy[ 15 ]. Of all VCE techniques, NBI has been studied most frequently for assessing gastroenterology diseases[ 40 ]. This pre-processing technique uses light of specific wavelengths (green - 540 nm and blue -415 nm) to enhance detail on the mucosal surface.…”

Artificial intelligence in inflammatory bowel disease endoscopy: current landscape and the road ahead

“… 4 A poor-quality endoscopy can lead to a delayed diagnosis and severe complications. 10 There is documented interobserver variation in pathologist diagnosis of IBD and then furthermore in differentiating between ulcerative colitis (UC) and Crohn’s disease (CD), even among specialized GI pathologists who are not available in most clinical centers. 9 For these reasons, serological, genetic, and inflammatory markers have become a focus of study for diagnosing IBD, differentiation of UC and CD, and grading severity of inflammation.…”