Language
English
Publication Date
6-1-2024
Journal
Surgical Endoscopy
DOI
10.1007/s00464-024-10858-z
PMID
38769187
PMCID
PMC11133140
PubMedCentral® Posted Date
5-20-2024
PubMedCentral® Full Text Version
Post-print
Abstract
Background: Soilage of the surgical endoscope occurs frequently during minimally invasive surgery. The resultant impairment of visualization of the surgical field compromises patient safety, prolongs operative times, and frustrates surgeons. The standard practice for cleaning the surgical camera involves a disruption in the conduct of surgery by completely removing the endoscope from the field, manually cleaning its lens, treating it with a surfactant, and reinserting it into the patient; after which the surgeon resumes the procedure.
Methods: We developed an automated solution for in vivo endoscope cleaning in minimally invasive surgery- a port that detects the position of the endoscope in its distal lumen, and precisely and automatically delivers a pressurized mist of cleaning solution to the lens of the camera. No additions to the scope and minimal user interaction with the port are required. We tested the efficacy of this troCarWash™ device in a porcine model of laparoscopy. Four board-certified general surgeons were instructed to soil and then clean the laparoscope using the device. Representative pre- and post-clean images were exported from the surgical video and clarity was graded (1) digitally by a canny edge detection algorithm, and (2) subjectively by 3 blinded, unbiased observers using a semi-quantitative scale.
Results: We observed statistically significant improvements in clarity by each method and for each surgeon, and we noted significant correlation between digital and subjective scores.
Conclusion: Based on these data, we conclude that the troCarWash™ effectively restored impaired visualization in a large animal model of laparoscopy.
Keywords
Laparoscopy, Animals, Swine, Laparoscopes, Equipment Contamination, Equipment Design, Minimally invasive surgery, Laparoscopic, Endoscopic, Visualization, Camera clean
Published Open-Access
yes
Recommended Citation
Ahmed, Maaz; Gowda, Ashok; Alavi Naini, Fatemeh; et al., "Quantitative Assessment of the troCarWash™ System for Automated Laparoscopic Camera Cleaning" (2024). Faculty, Staff and Students Publications. 6310.
https://digitalcommons.library.tmc.edu/baylor_docs/6310