Enhanced Laparoscopic Vision Improves Detection of Intraoperative Adverse Events During Laparoscopy

Enhancing surgeons' gaze strategies in endoscopic surgery during simulated surgical emergency situations thanks to computer vision. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083476 DOI: 10.1109/embc40787.2023.10340430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Deficient visualization in minimally invasive surgery often causes misperceptions, which can lead to an increase of iatrogenic lesions and complications. This is especially critical for novice surgeons, who are prone to adopt inadequate switching gaze strategies, thereby increasing the chance of unforeseen complications. In this paper the use of an additional computer-aided vision system was tested for improvement of the reaction of the surgeons to unforeseen complications. Gaze patterns were analyzed using a gaze tracker, as well as other metrics such as task completion time or reaction time to sudden bleeding. While completion time did not show significant difference between tested modalities (p<0.1), the reaction time showed a downward trend as more auxiliary computer-aided vision systems were added (p<0.005). These results support the benefits of including additional vision systems for minimally invasive surgery processes.Clinical Relevance- This work assesses the advantages of including an additional computer vision system to prevent unforeseen complications during minimally invasive surgeries.

Qualitative Comparison of Image Stitching Algorithms for Multi-Camera Systems in Laparoscopy

Multi-camera systems were recently introduced into laparoscopy to increase the narrow field of view of the surgeon. The video streams are stitched together to create a panorama that is easier for the surgeon to comprehend. Multi-camera prototypes for laparoscopy use quite basic algorithms and have only been evaluated on simple laparoscopic scenarios. The more recent state-of-the-art algorithms, mainly designed for the smartphone industry, have not yet been evaluated in laparoscopic conditions. We developed a simulated environment to generate a dataset of multi-view images displaying a wide range of laparoscopic situations, which is adaptable to any multi-camera system. We evaluated classical and state-of-the-art image stitching techniques used in non-medical applications on this dataset, including one unsupervised deep learning approach. We show that classical techniques that use global homography fail to provide a clinically satisfactory rendering and that even the most recent techniques, despite providing high quality panorama images in non-medical situations, may suffer from poor alignment or severe distortions in simulated laparoscopic scenarios. We highlight the main advantages and flaws of each algorithm within a laparoscopic context, identify the main remaining challenges that are specific to laparoscopy, and propose methods to improve these approaches. We provide public access to the simulated environment and dataset.

Improving vision for surgeons during laparoscopy: the Enhanced Laparoscopic Vision System (ELViS)

BACKGROUND

For many abdominal surgical interventions, laparotomy has gradually been replaced by laparoscopy, with numerous benefits for the patient in terms of post-operative recovery. However, during laparoscopy, the endoscope only provides a single viewpoint to the surgeon, leaving numerous blind spots and opening the way to peri-operative adverse events. Alternative camera systems have been proposed, but many lack the requisite resolution/robustness for use during surgery or cannot provide real-time images. Here, we present the added value of the Enhanced Laparoscopic Vision System (ELViS) which overcomes these limitations and provides a broad view of the surgical field in addition to the usual high-resolution endoscope.

METHODS

Experienced laparoscopy surgeons performed several typical procedure steps on a live pig model. The time-to-completion for surgical exercises performed by conventional endoscopy and ELViS-assisted surgery was measured. A debriefing interview following each operating session was conducted by an ergonomist, and a System Usability Scale (SUS) score was determined.

RESULTS

Proof of concept of ELVIS was achieved in an animal model with seven expert surgeons without peroperative adverse events related to the surgical device. No differences were found in time-to-completion. Mean SUS score was 74.7, classifying the usability of the ELViS as "good". During the debriefing interview, surgeons highlighted several situations where the ELViS provided a real advantage (such as during instrument insertion, exploration of the abdominal cavity or for orientation during close work) and also suggested avenues for improvement of the system.

CONCLUSIONS

This first test of the ELViS prototype on a live animal model demonstrated its usability and provided promising and useful feedback for further development.