Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis

Spadaccini, Marco; Iannone, Andrea; Maselli, Roberta; Badalamenti, Matteo; Desai, Madhav; Chandrasekar, Viveksandeep Thoguluva; Patel, Harsh K.; Fugazza, Alessandro; Pellegatta, Gaia; Galtieri, Piera Alessia; Lollo, Gianluca; Carrara, Sandro; Anderloni, Andrea; Rex, Douglas K.; Savevski, Victor; Wallace, Michael B.; Bhandari, Pradeep; Röesch, Thomas; Gralnek, Ian M.; Sharma, Prateek; Hassan, Cesare; Repici, Alessandro

doi:10.1016/s2468-1253(21)00215-6

Cited by 77 publications

(50 citation statements)

References 73 publications

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“…Various meta-analyses, that included randomized controlled trials (RCTs) comparing CADe-assisted colonoscopy with conventional colonoscopy (CC), have shown a significant increase in ADR in favor of CADe-assisted colonoscopy (33.7-36.6% versus 22.9-26.6%, respectively). Similarly, PDR also significantly increased in the CADe group compared to the CC group (45.6% versus 30.6%, respectively) [16][17][18].…”

Section: Introductionmentioning

confidence: 86%

Real-time colorectal polyp detection using a novel computer-aided detection system (CADe): a feasibility study

Soons¹,

Räth

Hazewinkel³

et al. 2022

Int J Colorectal Dis

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Background and aims Colonoscopy aims to early detect and remove precancerous colorectal polyps, thereby preventing development of colorectal cancer (CRC). Recently, computer-aided detection (CADe) systems have been developed to assist endoscopists in polyp detection during colonoscopy. The aim of this study was to investigate feasibility and safety of a novel CADe system during real-time colonoscopy in three European tertiary referral centers. Methods Ninety patients undergoing colonoscopy assisted by a real-time CADe system (DISCOVERY; Pentax Medical, Tokyo, Japan) were prospectively included. The CADe system was turned on only at withdrawal, and its output was displayed on secondary monitor. To study feasibility, inspection time, polyp detection rate (PDR), adenoma detection rate (ADR), sessile serrated lesion (SSL) detection rate (SDR), and the number of false positives were recorded. To study safety, (severe) adverse events ((S)AEs) were collected. Additionally, user friendliness was rated from 1 (worst) to 10 (best) by endoscopists. Results Mean inspection time was 10.8 ± 4.3 min, while PDR was 55.6%, ADR 28.9%, and SDR 11.1%. The CADe system users estimated that < 20 false positives occurred in 81 colonoscopy procedures (90%). No (S)AEs related to the CADe system were observed during the 30-day follow-up period. User friendliness was rated as good, with a median score of 8/10. Conclusion Colonoscopy with this novel CADe system in a real-time setting was feasible and safe. Although PDR and SDR were high compared to previous studies with other CADe systems, future randomized controlled trials are needed to confirm these detection rates. The high SDR is of particular interest since interval CRC has been suggested to develop frequently through the serrated neoplasia pathway. Clinical Trial Registration The study was registered in the Dutch Trial Register (reference number: NL8788).

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Section: Introductionmentioning

confidence: 86%

Real-time colorectal polyp detection using a novel computer-aided detection system (CADe): a feasibility study

Soons¹,

Räth

Hazewinkel³

et al. 2022

Int J Colorectal Dis

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“…Artificial intelligence (AI), and particularly deep learning, is increasingly used for computer-aided detection (CAD) of (pre)malignancies in endoscopic images. Multiple studies have shown that AI algorithms developed for image analysis in colonoscopy can successfully recognize (pre) malignant colonic lesions, as well as grade the inflammation status in IBD patients [76][77][78][79][80][81]. These results have already been translated to the clinic with the launch of the first commercially available AI system for colonoscopy in 2019 (GI Genius, Medtronic).…”

Section: Translation From Clinical Evidence To Clinical Usementioning

confidence: 99%

Highlighting the Undetectable — Fluorescence Molecular Imaging in Gastrointestinal Endoscopy

et al. 2022

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Flexible high-definition white-light endoscopy is the current gold standard in screening for cancer and its precursor lesions in the gastrointestinal tract. However, miss rates are high, especially in populations at high risk for developing gastrointestinal cancer (e.g., inflammatory bowel disease, Lynch syndrome, or Barrett’s esophagus) where lesions tend to be flat and subtle. Fluorescence molecular endoscopy (FME) enables intraluminal visualization of (pre)malignant lesions based on specific biomolecular features rather than morphology by using fluorescently labeled molecular probes that bind to specific molecular targets. This strategy has the potential to serve as a valuable tool for the clinician to improve endoscopic lesion detection and real-time clinical decision-making. This narrative review presents an overview of recent advances in FME, focusing on probe development, techniques, and clinical evidence. Future perspectives will also be addressed, such as the use of FME in patient stratification for targeted therapies and potential alliances with artificial intelligence. Key Messages • Fluorescence molecular endoscopy is a relatively new technology that enables safe and real-time endoscopic lesion visualization based on specific molecular features rather than on morphology, thereby adding a layer of information to endoscopy, like in PET-CT imaging. • Recently the transition from preclinical to clinical studies has been made, with promising results regarding enhancing detection of flat and subtle lesions in the colon and esophagus. However, clinical evidence needs to be strengthened by larger patient studies with stratified study designs. • In the future fluorescence molecular endoscopy could serve as a valuable tool in clinical workflows to improve detection in high-risk populations like patients with Barrett’s esophagus, Lynch syndrome, and inflammatory bowel syndrome, where flat and subtle lesions tend to be malignant up to five times more often. • Fluorescence molecular endoscopy has the potential to assess therapy responsiveness in vivo for targeted therapies, thereby playing a role in personalizing medicine. • To further reduce high miss rates due to human and technical factors, joint application of artificial intelligence and fluorescence molecular endoscopy are likely to generate added value.

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“…A recent network meta-analysis of 50 RCTs comprising 34,445 participants compared CADe with high-definition white light endoscopy, IEE techniques, and techniques that increased mucosal visualisation such as distal attachments and FUSE. (89) CADe was ranked as the superior technique for adenoma detection. Crosscomparisons of CADe with other imaging techniques showed a significant increase in the ADR with CADe versus increased mucosal visualisation systems (OR 1.54 [95% CI 1.22-1.94]; low certainty of evidence) and with CADe versus chromoendoscopy (OR 1.45 [95% CI 1.14-1.85]; moderate certainty of evidence).…”

Section: Integrating Ai-assisted Colonoscopy Into Current Clinical Pr...mentioning

confidence: 99%

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

Li¹,

Lm²

2022

smedj

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Colonoscopy is the reference standard procedure for the prevention and diagnosis of colorectal cancer, which is a leading cause of cancer-related deaths in Singapore. Artificial intelligence systems are automated, objective and reproducible. Artificial intelligence-assisted colonoscopy has recently been introduced into clinical practice as a clinical decision support tool. This review article provides a summary of the current published data and discusses ongoing research and current clinical applications of artificial intelligence-assisted colonoscopy.

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Computer-aided detection versus advanced imaging for detection of colorectal neoplasia: a systematic review and network meta-analysis

Cited by 77 publications

References 73 publications

Real-time colorectal polyp detection using a novel computer-aided detection system (CADe): a feasibility study

Real-time colorectal polyp detection using a novel computer-aided detection system (CADe): a feasibility study

Highlighting the Undetectable — Fluorescence Molecular Imaging in Gastrointestinal Endoscopy

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

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