Halvorsen, Natalie

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.

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.