East, James E.

Abstract The environmental impact of computer-aided diagnosis (CADx) in colonoscopy is unknown. The potential to reduce greenhouse gas emissions by limiting unnecessary polypectomies may be offset by emissions associated with CADx devices. We quantified and compared the carbon footprint of colonoscopy with and without CADx. Life-cycle carbon emissions associated with endoscopic snares, polyp traps, histopathology, and CADx devices were estimated using life-cycle assessment software. The effect of CADx was estimated by the carbon dioxide equivalent (CO2e) emissions related to outcomes from a prospective cohort of patients who underwent colonoscopy with optical diagnosis under a leave-in-situ strategy (i.e. rectosigmoid polyps ≤5 mm predicted as non-neoplastic were not removed) with and without CADx assistance. We analyzed 1134 individuals (median age 67 years, 59% male) with 1716 colorectal polyps. Colonoscopy with CADx reduced the number of snares and polyp traps from 567 to 543 (difference: 24) and histopathology submissions from 1343 to 1278 (difference: 65). However, the total carbon footprint increased from 832 kg CO2e (95%CI 815 to 847) without CADx to 946 kg CO2e (95%CI 927 to 965) with CADx, corresponding to an absolute increase of 114 kg CO2e (95%CI 80 to 150) or 0.10 kg CO2e per colonoscopy. Using CADx under a leave-in-situ strategy increased the environmental burden of colonoscopy.

Screening for colorectal cancer (CRC) is effective in reducing CRC related mortality. Current screening methods include endoscopy based and biomarker based approaches. This guideline is a joint official statement of the Asian Pacific Association of Gastroenterology (APAGE) and the Asian Pacific Society of Digestive Endoscopy (APSDE), developed in response to the increasing use of, and accumulating supportive evidence for the role of, non-invasive biomarkers for the diagnosis of CRC and its precursor lesions. A systematic review of 678 publications and a two stage Delphi consensus process involving 16 clinicians in various disciplines was undertaken to develop 32 evidence based and expert opinion based recommendations for the use of faecal immunochemical tests, faecal based tumour biomarkers or microbial biomarkers, and blood based tumour biomarkers for the detection of CRC and adenoma. Comprehensive up-to-date guidance is provided on indications, patient selection and strengths and limitations of each screening tool. Future research to inform clinical applications are discussed alongside objective measurement of research priorities. This joint APAGE–APSDE practice guideline is intended to provide an up-to-date guide to assist clinicians worldwide in utilising non-invasive biomarkers for CRC screening; it has particular salience for clinicians in the Asia-Pacific region.

The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost‐effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer‐aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health‐care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe‐related cancer prevention; Statement 1.4: Health‐care delivery systems and authorities should evaluate the cost‐effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer‐aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health‐care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health‐care delivery systems and authorities should evaluate the cost‐effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high‐quality cost‐effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health‐care systems.

Abstract Background Current guidelines recommend endoscopic resection of visible and endoscopically resectable colorectal colitis-associated neoplasia (CAN) in patients with inflammatory bowel disease (IBD). However, patients with high risk CAN are often not amenable to conventional resections techniques and a consensus approach for the endoscopic management of these lesions is presently lacking. This Delphi study aims to reach consensus amongst experts on the endoscopic management of these lesions. Methods A three-round modified Delphi process was conducted to reach consensus amongst worldwide IBD and/or endoscopy experts (n=18) from three continents. Experts were chosen based on the extensive clinical experience with IBD and/or EMR/ESD in patients with IBD, and the authorship on multiple peer-reviewed publications on CAN, the endoscopic resection of CAN and/or EMR/ESD. Consensus was considered if ≥ 75% agreed or disagreed. Quality of evidence was assessed by the criteria of the Cochrane Collaboration group. Results Consensus was reached on all statements (n=14). Experts agreed on a definition for CAN and high-risk CAN (HR-CAN). Consensus was reached on the examination of the colon with enhanced endoscopic imaging prior to resection, the endoscopic resectability of a HR-CAN lesion and endoscopic assessment and standard report of CAN lesions. In addition, experts agreed on type of resections of HR-CAN (< 20mm, >20 mm, with or without good lifting), endoscopic success (technical success and outcomes), histologic assessment and follow-up in HR-CAN. Conclusion This is the first step in developing international consensus-based recommendations for endoscopic management of (HR-)CAN. Although the quality of available evidence was considered low, consensus was reached on several aspects of the management of (HR-)CAN. The present work and proposed standardization might benefit future studies.

Abstract Background and Aims Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve, accelerate and automate UC detection, and predict the Mayo Endoscopic Subscore [MES] and the Ulcerative Colitis Endoscopic Index of Severity [UCEIS]. Methods A total of 134 prospective videos [1550 030 frames] were collected and those with poor quality were excluded. The frames were labelled by experts based on MES and UCEIS scores. The scored frames were used to create a preprocessing pipeline and train multiple convolutional neural networks [CNNs] with proprietary algorithms in order to filter, detect and assess all frames. These frames served as the input for the DL model, with the output being continuous scores for MES and UCEIS [and its components]. A graphical user interface was developed to support both labelling video sections and displaying the predicted disease severity assessment by the artificial intelligence from endoscopic recordings. Results Mean absolute error [MAE] and mean bias were used to evaluate the distance of the continuous model’s predictions from ground truth, and its possible tendency to over/under-predict were excellent for MES and UCEIS. The quadratic weighted kappa used to compare the inter-rater agreement between experts’ labels and the model’s predictions showed strong agreement [0.87, 0.88 at frame-level, 0.88, 0.90 at section-level and 0.90, 0.78 at video-level, for MES and UCEIS, respectively]. Conclusions We present the first fully automated tool that improves the accuracy of the MES and UCEIS, reduces the time between video collection and review, and improves subsequent quality assurance and scoring.

AbstractThe European Society of Gastrointestinal Endoscopy (ESGE) presents a short list of performance measures for colonoscopy in inflammatory bowel disease (IBD) patients. Current performance measures for colonoscopy mainly focus on detecting (pre)malignant lesions. However, these performance measures are not relevant for all colonoscopy indications in IBD patients. Therefore, our aim was to provide endoscopy services across Europe and other interested countries with a tool for quality monitoring and improvement in IBD colonoscopy. Eight key performance measures and one minor performance measure were recommended for measurement and evaluation in daily endoscopy practice.