Real-Time Artificial Intelligence–Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy

Barua, Ishita; Wieszczy, Paulina; Kudo, Shin‐ei; Misawa, Masashi; Holme, Øyvind; Gulati, Shraddha; Williams, Sophie; Mori, Kensaku; Itoh, Hayato; Takishima, Kazumi; Mochizuki, Kenichi; Miyata, Yuki; Mochida, Kentaro; Akimoto, Yoshika; Kuroki, Takanori; Morita, Yuriko; Shiina, Osamu; Kato, Sayuri; Nemoto, Tetsuo; Hayee, Bu; Patel, Mehul; Gunasingam, Nishmi; Kent, Alexandra; Emmanuel, Andrew; Munck, Carl; Nilsen, Jens Aksel; Hvattum, Stine Astrup; Frigstad, Svein Oskar; Tandberg, Petter; Løberg, Magnus; Kalager, Mette; Haji, Amyn; Bretthauer, Michael; Mori, Yuichi

doi:10.1056/evidoa2200003

Cited by 47 publications

(39 citation statements)

References 19 publications

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Section: Optical Diagnosis Of Polyps ≤ 5 MMmentioning

confidence: 99%

“…Only four real-time in vivo clinical trials are available that test CADx systems. Two trials 114 115 from the same Japanese group, using a CADx system and employing endocytomicroscopy and NBI, showed conflicting results, the first concluding that the system could meet required thresholds, while the second, in a multicenter setting with less experienced endoscopists, failed to reach acceptable levels. Another single-center study 116 involving 162 patients with 544 polyps showed that an approved CADx system exceeded PIVI thresholds for implementation in clinical practice, while a multicenter experience 117 with another approved CADx system fell short of required thresholds.…”

Section: Lower Gi Tractmentioning

confidence: 99%

“…Only four real-time in vivo clinical trials are available that test CADx systems. Two trials [114,115] from the same Japanese group, using a CADx system and employing endocytomicroscopy and NBI, showed conflicting results, the first concluding that the system could meet required thresholds, while the second, in a multicenter setting with less experienced endoscopists, failed to reach acceptable levels. Another single-center study RECOMMENDATION For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (≤ 5 mm), AIassisted characterization should match performance standards for implementing resect-and-discard and diagnose-and-leave strategies.…”

Section: Optical Diagnosis Of Polyps ≤ 5 MMmentioning

confidence: 99%

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Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

et al. 2022

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This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the diagnosis and management of gastrointestinal neoplasia within the framework of the performance measures already defined by ESGE. This is based on the clinical relevance of the expected task and the preliminary evidence regarding artificial intelligence in artificial or clinical settings. Main recommendations: (1) For acceptance of AI in assessment of completeness of upper GI endoscopy, the adequate level of mucosal inspection with AI should be comparable to that assessed by experienced endoscopists. (2) For acceptance of AI in assessment of completeness of upper GI endoscopy, automated recognition and photodocumentation of relevant anatomical landmarks should be obtained in ≥90% of the procedures. (3) For acceptance of AI in the detection of Barrett’s high grade intraepithelial neoplasia or cancer, the AI-assisted detection rate for suspicious lesions for targeted biopsies should be comparable to that of experienced endoscopists with or without advanced imaging techniques. (4) For acceptance of AI in the management of Barrett’s neoplasia, AI-assisted selection of lesions amenable to endoscopic resection should be comparable to that of experienced endoscopists. (5) For acceptance of AI in the diagnosis of gastric precancerous conditions, AI-assisted diagnosis of atrophy and intestinal metaplasia should be comparable to that provided by the established biopsy protocol, including the estimation of extent, and consequent allocation to the correct endoscopic surveillance interval. (6) For acceptance of artificial intelligence for automated lesion detection in small-bowel capsule endoscopy (SBCE), the performance of AI-assisted reading should be comparable to that of experienced endoscopists for lesion detection, without increasing but possibly reducing the reading time of the operator. (7) For acceptance of AI in the detection of colorectal polyps, the AI-assisted adenoma detection rate should be comparable to that of experienced endoscopists. (8) For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (≤5 mm), AI-assisted characterization should match performance standards for implementing resect-and-discard and diagnose-and-leave strategies. (9) For acceptance of AI in the management of polyps ≥ 6 mm, AI-assisted characterization should be comparable to that of experienced endoscopists in selecting lesions amenable to endoscopic resection.

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Section: Optical Diagnosis Of Polyps ≤ 5 MMmentioning

confidence: 99%

Section: Lower Gi Tractmentioning

confidence: 99%

Section: Optical Diagnosis Of Polyps ≤ 5 MMmentioning

confidence: 99%

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Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement

et al. 2022

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“…Recent evidence suggests that CADx tools are expected to reduce the number of polyp removals by identifying nonneoplastic polyps. 5 However, further development of CADx tools is hampered by a critical challenge, namely, unreliable pathologic diagnoses. The development of CADx needs accurate pathologic diagnoses of polyps that are used as criterion standard diagnoses for machine learning.…”

mentioning

confidence: 99%

“…The development of CADx needs accurate pathologic diagnoses of polyps that are used as criterion standard diagnoses for machine learning. 5 However, these pathologic diagnoses are subject to significant interobserver variability among pathologists (k coefficient range 0.4-0.7). [6][7][8] This precludes a correct labeling of polyp images to feed the computer.…”

mentioning

confidence: 99%