Feasibility study of intraoperative surgical navigation with focus on ureteral identification using the EVA system on an animal model.

Background: Ureteral injury (UI) stands as one of the most prevalent forms of iatrogenic urological injury. Currently, there is no non-invasive prevention strategy available to mitigate the risk of UI. Encouraging, though still in the preclinical phase, are investigations into the identification of ureters using ureter-specific vital dyes. Numerous studies are delving into the application of extended reality in the surgical fild. Our research team is in the process of validating surgical navigation utilizing the EVA system. This system introduces a dynamic extended reality (XR) environment that presents real-time 3D models of patient-specific organs superimposed and synchronized with the endoscopic view during surgery. Our aims is to validate surgical navigation with the EVA system in a biological context and apply it for ureters identification. Materials and Methods: A trained surgeon evaluated the setting and the calibration between the images from the endoscope and 3D models. The startup and installation times, integration into the operating room, system usability and calibration errors were analyzed. Than four surgeons identified the ureters with and without the EVA system. Their experience was assessed through questionnaires. Results: The system is safe and easily integrable with the operating room instruments. The error after automatic calibration remains significant but is easily correctable with manual calibration. The virtual ureter overlaps with the real ureter. The questionnaires highlight that surgeons appreciated the EVA navigation system, integrating well as a supportive tool alongside traditional instrumentation. Conclusions: This study demonstrates how surgical navigation in a biological and in vivo setting is possible through the EVA system. The virtual ureter overlaps with the real ureter, leading us to consider it as a valuable aid for its identification in complex fields. Further studies are needed to reduce the error of automatic calibration and minimize the need for manual calibration.