Development and validation of artificial neural networks model for detection of Barrett’s neoplasia: a multicenter pragmatic nonrandomized trial (with video)

Abdelrahim, Mohamed; Saiko, Masahiro; Maeda, Naoto; Hossain, Ejaz; Alkandari, Asma; Subramaniam, Sharmila; Parra‐Blanco, Adolfo; Sánchez-Yagüe, Andrés; Coron, Emmanuel; Repici, Alessandro; Bhandari, Pradeep

doi:10.1016/j.gie.2022.10.031

Cited by 26 publications

(16 citation statements)

References 24 publications

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“…Former AI trials on BE have usually compared the standalone performance of AI with the performance of endoscopists [28,29]. However, the stand-alone performance is only a small fraction of the equation because endoscopists may or may not follow the suggestions of AI.…”

Section: Discussionmentioning

confidence: 99%

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

Meinikheim,

Mendel,

Palm

et al. 2024

Endoscopy

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Background and study aims To evaluate the effect of an AI-based clinical decision support system (AI) on the performance and diagnostic confidence of endoscopists during the assessment of Barrett's esophagus (BE). Patients and Methods Ninety-six standardized endoscopy videos were assessed by 22 endoscopists from 12 different centers with varying degrees of BE experience. The assessment was randomized into two video sets: Group A (review first without AI and second with AI) and group B (review first with AI and second without AI). Endoscopists were required to evaluate each video for the presence of Barrett's esophagus-related neoplasia (BERN) and then decide on a spot for a targeted biopsy. After the second assessment, they were allowed to change their clinical decision and confidence level. Results AI had a standalone sensitivity, specificity, and accuracy of 92.2%, 68.9%, and 81.6%, respectively. Without AI, BE experts had an overall sensitivity, specificity, and accuracy of 83.3%, 58.1 and 71.5%, respectively. With AI, BE nonexperts showed a significant improvement in sensitivity and specificity when videos were assessed a second time with AI (sensitivity 69.7% (95% CI, 65.2% - 74.2%) to 78.0% (95% CI, 74.0% - 82.0%); specificity 67.3% (95% CI, 62.5% - 72.2%) to 72.7% (95 CI, 68.2% - 77.3%). In addition, the diagnostic confidence of BE nonexperts improved significantly with AI. Conclusion BE nonexperts benefitted significantly from the additional AI. BE experts and nonexperts remained below the standalone performance of AI, suggesting that there may be other factors influencing endoscopists to follow or discard AI advice.

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Section: Discussionmentioning

confidence: 99%

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

Meinikheim,

Mendel,

Palm

et al. 2024

Endoscopy

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“…Conclusions This is the first real-world experience demonstrating the potential value of AI-assisted targeted biopsies in Barrett’s neoplasia surveillance. The specificity of AI neoplasia detection is less compared to previously published pre-clinical studies, highlighting the need to address the issue of false positive predictions by AI 1 .…”

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confidence: 82%

Is AI ready to replace protocol guided biopsies in Barrett’s surveillance? The first real-world experience

Abdelrahim,

Htet,

Siggens

et al. 2023

ESGE Days 2023

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“…Detailed characterization requires expertise or AI. Abdelrahim et al [21], a multicenter study was carried out for the detection and localization of Barrett's neoplasia and assess its performance compared with that of general endoscopists in a statistically powered multicenter study by using real-time video sequences. CAD system was tested on six nonexpert endoscopist with positive results.…”

Section: Artificial Intelligence For Esophagus Diseasesmentioning

confidence: 99%

Artificial intelligence in digestive endoscopy: recent advances

Rey

2023

Current Opinion in Gastroenterology

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Purpose of review With the incessant advances in information technology and its implications in all domains of our life, artificial intelligence (AI) started to emerge as a need for better machine performance. How it can help endoscopists and what are the areas of interest in improving both diagnostic and therapeutic endoscopy in each part of the gastrointestinal (GI) tract. What are the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. Recent Findings The two main AI systems categories are computer-assisted detection ‘CADe’ for lesion detection and computer-assisted diagnosis ‘CADx’ for optical biopsy and lesion characterization. Multiple softwares are now implemented in endoscopy practice. Other AI systems offer therapeutic assistance such as lesion delineation for complete endoscopic resection or prediction of possible lymphanode after endoscopic treatment. Quality assurance is the coming step with complete monitoring of high-quality colonoscopy. In all cases it is a computer-aid endoscopy as the overall result rely on the physician. Video capsule endoscopy is the unique example were the computer conduct the device, store multiple images, and perform accurate diagnosis. Summary AI is a breakthrough in digestive endoscopy. Screening gastric and colonic cancer detection should be improved especially outside of expert's centers. Prospective and multicenter trials are mandatory before introducing new software in clinical practice.

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Development and validation of artificial neural networks model for detection of Barrett’s neoplasia: a multicenter pragmatic nonrandomized trial (with video)

Cited by 26 publications

References 24 publications

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

Is AI ready to replace protocol guided biopsies in Barrett’s surveillance? The first real-world experience

Artificial intelligence in digestive endoscopy: recent advances

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