Clinical Validation of Polydeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System

Overview

This study is a clinical validation of Polydeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. Polydeep Advance 1 is an unicentric prospective diagnostic tests trial with a paired study design. The hypothesis of the study is that Polydeep, a CAD system, is more sensitive than a blinded endoscopists for the detection of colorectal polyps in a high definition colonoscopy.

Colorectal cancer (CRC) is the most frequently cancer in western world. A fundamental tool for detection and prevention is the colonoscopy. The detection and endoscopic resection of colorectal polyps, the precursor lesion of CRC can reduce CRC incidence and mortality. Adenoma detection rate is the most used endoscopic quality indicator. The improvement of this indicator is related to the reduction of postcolonoscopy CRC incidence and mortality. Colorectal polyp diagnosis is based on endoscopic resection and histological analysis. An accurate optical diagnosis could avoid histological lesion of smaller lesions, reducing the costs associated with histological diagnosis. The NICE international classification has proposed the use of high definition endoscopes that have Narrow Band Imaging. However, NICE must be used by endoscopists who are sufficiently prepared and who have overcome the learning curve. Therefore, optical histology diagnosis with high accuracy independently of the center and the endoscopist is necessary. Computer Aid Diagnosis (CAD) systems based on Artificial Intelligence are experiencing exponential development in the field of medical image analysis. The development of the CAD system is based on the creation of large databases of endoscopic images and/or videos, on the training, development and validation of diagnostic algorithms in such databases and, finally, on prospective clinical validation in patients undergoing colonoscopy. The goal of CAD systems in colonoscopy is double. First, it aims to increase the detection of polyps (CADe) in general, and of adenomas and serrated lesions in particular. The second objective is to characterize (CADx) the histology of detected lesion. Polydeep CAD is a functional prototype. It is capable of detecting, locating and classifying colorectal polyps. In vivo validation data shows that Polydeep has high diagnostic accuracy for polyp identification and that this accuracy can be accommodated. The aim of Polydeep advance 1 is to perform the clinical validation within a diagnostic test trial with a paired study design. We will compare the sensitivity of Polydeep to endoscopists blinded to Polydeep in high definition colonoscopy.

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