AI-Based Stool Image Analysis for Colorectal Neoplasia Risk Assessment

Overview

This prospective observational substudy evaluates the association between artificial intelligence-derived features from stool images analyzed using the FAEX Health digital platform and fecal immunochemical test results in adults undergoing colorectal cancer screening or diagnostic evaluation. Participants will capture stool images using a mobile application. The primary analysis will compare AI-derived image outputs with quantitative FIT values and FIT positivity. Secondary exploratory analyses will assess associations with colonoscopy and histopathological findings when these results are available. The platform will be used exclusively for research and will not provide diagnoses, replace clinical evaluation, or influence medical decisions.

This is a substudy of the project "Estrategia de prevención secundaria de cáncer colorrectal en personas mayores a 18 años." The substudy evaluates the FAEX Health digital platform, which applies artificial intelligence algorithms to stool images for non-diagnostic research and validation. Participants will capture images of their stools using the FAEX Health mobile application. The images will be coded and analyzed using computational algorithms designed to identify visual characteristics such as color, consistency, and possible visible blood. The primary objective is to evaluate the association and discriminatory performance of AI-derived stool image features for quantitative fecal immunochemical test results and FIT positivity. Secondary exploratory objectives are to assess associations between these image features and colonoscopic and histopathological findings among participants for whom these results are available. The AI-derived results will not be returned to participants or treating clinicians and will not be used to determine whether colonoscopy or any other clinical procedure is performed. The findings may inform future studies evaluating stool image analysis as a potential triage strategy when FIT is unavailable or declined; however, the present study does not evaluate the platform as a replacement for FIT. Personal identifiers will not be stored together with stool images. Access to coded study information will be restricted to authorized researchers, and study data will be managed according to applicable ethical, legal, and confidentiality requirements.