Multicenter Study Comparing AI-Based Navicam vs. Conventional Pillcam in Small Bowel Pathology

Overview

Since its introduction in 2001, small bowel capsule endoscopy has been pivotal in diagnosing small bowel pathology due to its minimally invasive nature and high diagnostic accuracy. However, the technology has limitations, including prolonged reading times and the need for specialized endoscopists. The Navicam endoscopic capsule, leveraging artificial intelligence (AI) with ProScan™ for automated reading, promises to address these limitations by reducing reading times and enhancing diagnostic efficiency. This study aims to assess the diagnostic concordance and to compare the efficiency of the AI-based Navicam capsule with the conventional Pillcam SB3 in the exploration of the small bowel.

This is a prospective, multicenter, randomized, observational study involving multiple hospitals across Spain. At each site, patients will ingest both the Pillcam SB3 and Navicam capsules in a randomized order. Reading times, transit times, and diagnostic yield will be compared between the two devices. A central reading committee of experienced gastroenterologists will conduct blinded evaluations of both explorations using predefined criteria. The primary endpoint is the diagnostic concordance between Navicam's AI-driven ProScan™ system and the conventional reading of Pillcam SB3, measured by Cohen's kappa index. The secondary endpoints include to assess the correlation in lesion detection, video download times, gastric and small bowel transit times, total reading times, and adverse events. The sample size is 147 patients, accounting for an expected 10% dropout rate, based on previous studies showing a diagnostic concordance kappa index of 0.6. This study aims to establish that the AI-based Navicam capsule is at least as effective as the conventional Pillcam SB3 in diagnosing small bowel lesions, with potentially reduced reading times, thus enhancing clinical efficiency in small bowel diagnostics.