Robot-assisted and fluorescence-guided remnant-cholecystectomy: a prospective dual-center cohort study.

BACKGROUND: Abdominal symptoms after cholecystectomy may be caused by gallstones in a remnant gallbladder or a long cystic duct stump. Resection of a remnant gallbladder or cystic duct stump is associated with an increased risk of conversion and bile duct or vascular injuries. We prospectively investigated the additional value of robotic assistance and fluorescent bile duct illumination in redo biliary surgery. METHODS: In this prospective two-centre observational cohort study, 28 patients were included with an indication for redo biliary surgery because of remnant stones in a remnant gallbladder or long cystic duct stump. Surgery was performed with the da Vinci X® and Xi® robotic system. The biliary tract was visualised in the fluorescence Firefly® mode shortly after intravenous injection of indocyanine green. RESULTS: There were no conversions or perioperative complications, especially no vascular or bile duct injuries. Fluorescence-based illumination of the extrahepatic bile ducts was successful in all cases. Symptoms were resolved in 27 of 28 patients. Ten patients were treated in day care and 13 patients were discharged the day after surgery. CONCLUSION: Robot-assisted fluorescence-guided surgery for remnant gallbladder or cystic duct stump resection is safe, effective and can be done in day-care setting.

Fluorescence-Based Quantification of Gastrointestinal Perfusion: A Step Towards an Automated Approach.

Background: Qualitative fluorescence angiography (FA) provides insights into intestinal tissue perfusion, but today it is not yet accurate in predicting anastomotic leakage. To improve peroperative detection of impaired perfusion, quantified parameters should be investigated using a standardized method. The aim of this study was to develop a (semi)automated algorithm for comprehensive and convenient analysis of FA parameters. Materials and Methods: An analysis tool was developed for the extraction of quantified FA parameters. The start- and endpoint of intensity increase (T0 and Tmax) were automatically detected in the intensity-time curves. Algorithm performance was measured against manual assignment of T0 and Tmax by 9 independent observers in 18 in vivo generated test signals, using the intraclass correlation coefficient (ICC). Characteristics of parameter T1∕2 (time to 50% of maximal intensity) were analyzed in normally perfused small intestine of 32 subjects who underwent robotic laparoscopic surgery. Since ethical approval was not required under the Dutch law, the need for informed consent was waived. Results: Automated detection of T0 and Tmax was successful in all subjects. Output of the algorithm had an excellent agreement with the median of the human observations: ICC = 0.95 (95% confidence interval: 0.86-0.96). Overall, T1∕2 had a median value of 5.1 (interquartile range = 2.4) seconds and a minimal and maximal value of 1.3 and 9.9 seconds, respectively. Conclusions: The presented method provided convenient data analysis in the search for effective FA quantification. Future research should expand the data to find adequate threshold values for peroperatively identifying insufficient perfusion and investigate the influence of physiological conditions.