Artificial Intelligence and Endoscopist Diagnostic Agreement as a Framework for Colorectal Polyp Optical Diagnosis Implementation

Abstract

Aims Artificial intelligence (AI) has enabled the development of computer-aided diagnosis (CADx) systems which offer real-time endoscopic pathology prediction of colorectal polyps [ 1 ]. However, the clinical benefit of CADx assisted optical diagnosis remains questionable due to limited diagnostic improvement compared to CADx unassisted optical diagnosis [ 2 ]. This study aimed to assess diagnostic performance of a novel CADx implementation framework in which the high/low endoscopist confidence-based approach was replaced by a CADx and endoscopist agreement-based approach. Methods We performed a secondary analysis of a large prospective cohort undergoing optical polyp diagnosis at our center. Polyps measuring≤5mm (diminutive) with available CADx unassisted and CADx assisted optical polyp diagnosis documentation were included in our analysis. For CADx assisted cases, first the CADx diagnostic output was documented, followed by the endoscopist’s final diagnosis after seeing the CADx output. Only cases where endoscopist and CADx agreed on a diagnosis were retained. Primary outcome was sensitivity for adenoma diagnosis of CADx assisted optical diagnosis based on the agreement framework versus CADx unassisted optical diagnosis, using pathology results as a reference standard. Secondary outcomes included accuracy, diagnostic characteristics, and optical diagnosis surveillance interval agreement with pathology-based United States Multi-Society Task Force (USMSTF) guidelines. Results…