Artificial intelligence-assisted colonoscopy: a narrative review of current data and clinical applications

Li, Weiquan; Lm, Wang

doi:10.11622/smedj.2022044

Cited by 7 publications

(4 citation statements)

References 96 publications

(96 reference statements)

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“…Computer-aided diagnosis (CADx) systems can provide endoscopists with an automated real-time output for the characterization of polyps detected during colonoscopy. 78,79 In a study by Minegishi et al, 80 the real-time use of a CADx system when paired with endoscopist high-confidence optical diagnosis using NBI achieved an NPV for adenomatous histology of 94.1% (95% CI 83.8-98.8%) in diminutive rectosigmoid colon polyps. The COMBO-CAD study, 81 which was designed as a single-center, head-to-head noninferiority comparison of two commercially available CADx systems, similarly demonstrated high NPVs for adenomatous histology in diminutive rectosigmoid colon polyps (97.0% and 97.7%).…”

Section: Colorectal Polyps and Cancermentioning

confidence: 99%

“…Computer‐aided diagnosis (CADx) systems can provide endoscopists with an automated real‐time output for the characterization of polyps detected during colonoscopy 78,79 . In a study by Minegishi et al ., 80 the real‐time use of a CADx system when paired with endoscopist high‐confidence optical diagnosis using NBI achieved an NPV for adenomatous histology of 94.1% (95% CI 83.8–98.8%) in diminutive rectosigmoid colon polyps.…”

Section: Colorectal Polyps and Cancermentioning

confidence: 99%

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Precision endoscopy in the era of climate change and sustainability

Ueda,

Li,

et al. 2023

J of Gastro and Hepatol

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Global warming caused by increased greenhouse gas (GHG) emissions has a direct impact on human health. Gastrointestinal (GI) endoscopy contributes significantly to GHG emissions due to energy consumption, reprocessing of endoscopes and accessories, production of equipment, safe disposal of biohazardous waste, and travel by patients. Moreover, GHGs are also generated in histopathology through tissue processing and the production of biopsy specimen bottles. The reduction in unnecessary surveillance endoscopies and biopsies is a practical approach to decrease GHG emissions without affecting disease outcomes. This narrative review explores the role of precision medicine in GI endoscopy, such as image‐enhanced endoscopy and artificial intelligence, with a focus on decreasing unnecessary endoscopic procedures and biopsies in the surveillance and diagnosis of premalignant lesions in the esophagus, stomach, and colon. This review offers strategies to minimize unnecessary endoscopic procedures and biopsies, decrease GHG emissions, and maintain high‐quality patient care, thereby contributing to sustainable healthcare practices.

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Section: Colorectal Polyps and Cancermentioning

confidence: 99%

Section: Colorectal Polyps and Cancermentioning

confidence: 99%

Precision endoscopy in the era of climate change and sustainability

Ueda,

Li,

et al. 2023

J of Gastro and Hepatol

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“…CADx involves characterizing polyps based on morphological parameters, such as surface, vascular patterns, shape, size, and location, to generate probability scores for malignancy or nonmalignancy [ 41 ]. This helps to improve the accuracy of optical biopsies, which refer to the in vivo prediction of polyp histology before resection and formal histological analysis [ 42 ]. Most of these systems use image-enhanced endoscopy techniques such as narrow-band imaging and blue laser imaging (BLI) to enhance the accuracy of predictions.…”

Section: Ai In Colonoscopymentioning

confidence: 99%

The imitation game: a review of the use of artificial intelligence in colonoscopy, and endoscopists’ perceptions thereof

Tham¹,

Koh²,

Ladlad³

et al. 2023

Ann Coloproctol

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The development of deep learning systems in artificial intelligence (AI) has enabled advances in endoscopy, and AI-aided colonoscopy has recently been ushered into clinical practice as a clinical decision-support tool. This has enabled real-time AI-aided detection of polyps with a higher sensitivity than the average endoscopist, and evidence to support its use has been promising thus far. This review article provides a summary of currently published data relating to AI-aided colonoscopy, discusses current clinical applications, and introduces ongoing research directions. We also explore endoscopists’ perceptions and attitudes toward the use of this technology, and discuss factors influencing its uptake in clinical practice.

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“…In gastrointestinal endoscopy, technology advancement is expressing its maximum potential. The application of artificial intelligence, new techniques, such as submucosal dissection, full thickness resections, and others, are now a reality and we are only at the beginning of the noninvasive treatment of several diseases that once required surgical resection [ 11 ].…”

mentioning

confidence: 99%