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Review
. 2023 Nov 7;11(11):2991.
doi: 10.3390/biomedicines11112991.

Enteroscopy versus Video Capsule Endoscopy for Automatic Diagnosis of Small Bowel Disorders-A Comparative Analysis of Artificial Intelligence Applications

Stefan Lucian Popa  1 , Bogdan Stancu  2 , Abdulrahman Ismaiel  1 , Daria Claudia Turtoi  3 , Vlad Dumitru Brata  3 , Traian Adrian Duse  3 , Roxana Bolchis  3 , Alexandru Marius Padureanu  3 , Miruna Oana Dita  3 , Atamyrat Bashimov  3 , Victor Incze  3 , Edoardo Pinna  3 , Simona Grad  1 , Andrei-Vasile Pop  1 , Dinu Iuliu Dumitrascu  4 , Mihai Alexandru Munteanu  5 , Teodora Surdea-Blaga  1 , Florin Vasile Mihaileanu  2
Affiliations
Review

Enteroscopy versus Video Capsule Endoscopy for Automatic Diagnosis of Small Bowel Disorders-A Comparative Analysis of Artificial Intelligence Applications

Stefan Lucian Popa et al. Biomedicines. .

Abstract

Background: Small bowel disorders present a diagnostic challenge due to the limited accessibility of the small intestine. Accurate diagnosis is made with the aid of specific procedures, like capsule endoscopy or double-ballon enteroscopy, but they are not usually solicited and not widely accessible. This study aims to assess and compare the diagnostic effectiveness of enteroscopy and video capsule endoscopy (VCE) when combined with artificial intelligence (AI) algorithms for the automatic detection of small bowel diseases.

Materials and methods: We performed an extensive literature search for relevant studies about AI applications capable of identifying small bowel disorders using enteroscopy and VCE, published between 2012 and 2023, employing PubMed, Cochrane Library, Google Scholar, Embase, Scopus, and ClinicalTrials.gov databases.

Results: Our investigation discovered a total of 27 publications, out of which 21 studies assessed the application of VCE, while the remaining 6 articles analyzed the enteroscopy procedure. The included studies portrayed that both investigations, enhanced by AI, exhibited a high level of diagnostic accuracy. Enteroscopy demonstrated superior diagnostic capability, providing precise identification of small bowel pathologies with the added advantage of enabling immediate therapeutic intervention. The choice between these modalities should be guided by clinical context, patient preference, and resource availability. Studies with larger sample sizes and prospective designs are warranted to validate these results and optimize the integration of AI in small bowel diagnostics.

Conclusions: The current analysis demonstrates that both enteroscopy and VCE with AI augmentation exhibit comparable diagnostic performance for the automatic detection of small bowel disorders.

Keywords: artificial intelligence; enteroscopy; small bowel; video capsule endoscopy.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
PRISMA flow diagram for study selection.
Figure 2
Figure 2
QUADAS-2 framework evaluating the risk of bias of studies focused on capsule endoscopy [12,13,14,15,16,17].
Figure 3
Figure 3
QUADAS-2 framework evaluating the risk of bias of studies focused enteroscopy [18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38].
See this image and copyright information in PMC

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