Computer aided detection and diagnosis of polyps in adult patients undergoing colonoscopy: a living clinical practice guideline
Abstract
Abstract Clinical question In adult patients undergoing colonoscopy for any indication (screening, surveillance, follow-up of positive faecal immunochemical testing, or gastrointestinal symptoms such as blood in the stools) what are the benefits and harms of computer-aided detection (CADe)? Context and current practice Colorectal cancer (CRC), the third most common cancer and the second leading cause of cancer-related death globally, typically arises from adenomatous polyps. Detection and removal of polyps during colonoscopy can reduce the risk of cancer. CADe systems use artificial intelligence (AI) to assist endoscopists by analysing real-time colonoscopy images to detect potential polyps. Despite their increasing use in clinical practice, guideline recommendations that carefully balance all patient-important outcomes remain unavailable. In this first iteration of a living guideline, we address the use of CADe at the level of an individual patient. Evidence Evidence for this recommendation is drawn from a living systematic review of 44 randomised controlled trials (RCTs) involving more than 30 000 participants and a companion microsimulation study simulating 10 year follow-up for 100 000 individuals aged 60-69 years to assess the impact of CADe on patient-important outcomes. While no direct evidence was found for critical outcomes of colorectal cancer incidence and post-colonoscopy cancer incidence, low certainty data from the trials indicate that CADe may increase…
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