Exploring the Impact of an Artificial Intelligence-Based Intraoperative Image Navigation System in Laparoscopic Surgery on Clinical Outcomes: A Protocol for a Multicenter Randomized Controlled Trial.

ABSTRACT:

Introduction

Artificial intelligence (AI), particularly deep learning-based computer vision technology, has been used in surgery as real-time intraoperative navigation; however, its clinical relevance remains unclear. To address this gap, well-designed randomized controlled trials (RCTs) are necessary to evaluate the effects of these systems by comparing surgical outcomes with and without their use. In this study, we will investigate a deep learning-based intraoperative image navigation system that operates in real time and uses semantic segmentation to help identify the ureter and autonomic nerves during laparoscopic colorectal surgery. We propose a multicenter RCT to compare the procedure of using this system against those that do not.

Methods

The ImNavi trial is a Japanes

SUBMITTER: Kitaguchi D 

PROVIDER: S-EPMC12823098 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature