Surveillance for colorectal cancer (CRC) in patients predisposed to develop CRC during their lifetime has been impacted by access to colonoscopy suites and endoscopy specialists in the past couple of years. An alternative method, namely the colon capsule, has been proposed, however this investigation is time consuming for the clinician and the images require up to one hour (30-60 minutes) reading to issue a result. The investigators propose to obtain images from paired colonoscopies and colon capsules with the purpose of developing an AI algorithm which could aid the clinicians in reading the colon and expand access to this investigation. The main aim of the study is to determine whether it is possible to obtain usable paired images from patients with Lynch and other cancer predisposition syndromes. This will depend on the willingness of the patients to take part in the study and the technical ability of obtaining data from paired images of colonoscopies and colon capsule. At recruitment, participants will undergo a colon capsule investigation, followed by a routine colonoscopy as per their normal standard of care. Paired endoscopic images from colonoscopies and colon capsules will be collected and anonymised data will be accessed by the bioinformatician for analysis. If the study will be successful in reaching the primary endpoint, further trials will be opened, allowing for a larger population to be included and to obtain more robust data, which eventually can lead to validated AI algorithms and application of computer-aided video-capsules examination as a screening tool in at-risk population.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
The proportion of paired images the bioinformatician assesses as useful for the development of algorithm
Timeframe: 18 months