Colorectal cancer

Computer science

Colonoscopy

Colorectal Polyp

Internal medicine

Artificial intelligence

Medicine

Gastroenterology

General surgery

Cancer

To improve colorectal polyp detection, a new artificial intelligence (AI) system (GI-Genius, Medtronic) was trained and validated on a dataset of white-light endoscopy videos from a high-quality randomised controlled trial in comparison to the detection rate and the reaction time (RT) on a lesion basis (n=337/338, sensitivity: 99.7%); false-positive frames were seen in less than 1% of frames from the whole colonoscopy. The RT was faster by AI system as compared with endoscopists in 82% of cases (n=277/337; difference 1.27+3.81 s). This promising system will be tested in clinical studies.Despite its efficacy in colorectal cancer prevention, colonoscopy is affected by a high miss rate of neoplastic lesions and unacceptable variability in adenoma detection rate among individual endoscopists.1 2 By aiding polyp detection on colonoscopy images (figure 1), artificial intelligence (AI) can reduce performance variability. AI algorithms for object detection usually comprise a convolutional neural network trained using as ground truth images annotated by experts. Once trained, these AI systems are able to detect and pinpoint objects in real time, such as colorectal polyps. A new AI system (GI-Genius, Medtronic) was trained and validated using a series of videos of 2684 histologically confirmed polyps from 840 patients who underwent high-definition white-light colonoscopy as part of a previous randomised controlled study with centralised pathology.3 A total of 1.5 million images showing these polyps from different perspectives were extracted from videos and manually annotated by expert endoscopists. For the purpose of the study, patients were randomised between a validation group and a training group. In detail, for the validation phase, 338 polyps (168/338 adenomas or sessile serrated adenomas, 49.7%) from 105 patients were used. For each of these polyps, a video clip was cut starting 5 s before polyp appearance and ending when the snare/biopsy forceps appeared. To assess sensitivity, a true-positive per …

New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection