Laparoscopic Augmented Reality for Identification of Liver Lesions - a Pre-clinical Randomized Cross-over Trial

Augmented Reality, Laparoscopy, Liver, Orientation, Spatial

Augmented reality, liver, minimally invasive surgery, laparoscopy, 3D, spatial orientation, digital health, artificial intelligence

Procedure preparation and accurate knowledge of the specific anatomy is an integral part of performing minimally invasive procedures. Due to the complexity with high variability and the non-visibility of the vascular structures, the liver poses a particular challenge. Therefore medical students and experienced surgeons will receive standardized, structured training on liver anatomy, the use of laparoscopic ultrasound and the application and use of CT data sets and the virtual 3D liver model. This training will be evaluated by questionnaires. Both groups then carry out a series of localization exercises on an artificial liver phantom: tumor imitations, which are displayed in the image(3D virtaul mdoel or 2D-CT-Data-Set), have to be found in the liver phantom laparoscopically using ultrasound. In each round, different scenarios are worked on, once without and then with the support of the virtual 3D liver model. The virtual 3D model can be displayed directly on the laparoscopic monitor using a display software specially developed for the trial and can be manipulated by the subjects. The aim of the study is to provide evidence that the availability and use of a virtual 3D model (augmented reality) leads to a significantly improved spatial perception of the subjects during laparoscopy of the liver. In addition, the subjectively perceived cognitive load of the subjects during the test run with and without the support of the virtual 3D model is surveyed and the learning success is evaluated.

Procedure preparation and accurate knowledge of the specific anatomy is an integral part of performing a minimally invasive procedure. Due to the complexity with high variability and the non-visibility of the vascular structures due to the location in the parenchyma, the liver poses a particular challenge. The spatial perception and cognitive processing of the anatomical target structures is of particular importance. The aim of this study is to test the hypothesis that the use of a 3-dimensional (3D) virtual liver model (virtual 3D model crating augmented reality) presenedt on teh laparoscopic screeen reconstructed from CT data exerts an influence on the spatial perception of subjects during laparoscopy on the liver phantom. After informed consent and consent to the study, a pseudonymised subject population consisting of surgeons with experience in laparoscopy (n=36) and an equal number of medical students without experience in laparoscopy (n=36) will be included in the study included. The subjects will be randomized and divided into two groups of equal size, stratified according to experience in laparoscopy. The randomization is carried out by a data trustee. All subjects then receive standardized, structured training on liver anatomy, the use of laparoscopic ultrasound, and the application and use of CT data sets and the virtual 3D liver model. This is evaluated by means of a questionnaire. Both groups then sequentially carry out a defined series of localization exercises on an artificial liver phantom: tumor imitations, which are displayed in the image, have to be found in the liver phantom laparoscopically using ultrasound. In each round, different scenarios are worked on once without and then with the support of the virtual 3D liver model. The virtual 3D model can be displayed directly on the laparoscopic monitor using display software specially made for the study and can be manipulated by the subjects. The aim of the study is to provide evidence that the availability and use of a virtual 3D model leads to a significantly improved spatial perception of the subjects during laparoscopy of the liver. In addition, the subjectively perceived cognitive load of the subjects during the test run with and without the support of the virtual 3D model is surveyed by NASA Task Load Index and the learning success is evaluated. The primary endpoints of the study are the number of correctly spatially identified target structures and the time required to localize the given target structures.

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