AI trained to detect hard to spot cancerous lesions in colon

An artificial intelligence (AI) tool, developed by scientists at UCL, UCLH and UCL-spinout Odin Vision, has been further refined to identify hard to spot 'flat' polyps, that - when left untreated - can become highly aggressive and are a major cause of colorectal (bowel) cancer. For the study, published last year in Digestive Endoscopy, the research team trained the AI in Odin Vision's CADDIE system on these flat polyps. CADDIE uses AI during an endoscopy to detect and characterise adenomatous polyps (AP) in real-time. APs are more common and have distinctive tubular features with the growth resembling a mushroom, attached to the colon by a thin stalk. In comparison flat polyps, including flat lesions and sessile serrated lesions (SSLs) , known as 'subtle advanced neoplasia', have far fewer distinctive features and are notoriously difficult to detect. They are also more likely to develop into an aggressive cancer, meaning it will spread or grow quickly. To overcome this, researchers upgraded the CADDIE AI algorithm and created four video test datasets, containing images of 173 polyps (consisting of more than 670,000 individual frames), that included a dataset of the most challenging flat polyps.