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Surg Endosc ; 30(7): 3128-32, 2016 07.
Article in English | MEDLINE | ID: mdl-26487207

ABSTRACT

INTRODUCTION: Bile leakage is a serious complication occurring in up to 10 % of hepatic resections. Intraoperative detection of bile leakage is challenging, and concomitant blood oozing can mask the presence of bile. Intraductal dye injection [methylene blue or indocyanine green (ICG)] is a validated technique to detect bile leakage. However, this method is time-consuming, particularly in the laparoscopic setting. A novel narrow band imaging (NBI) modality (SPECTRA-A; Karl Storz, Tuttlingen, Germany) allows easy discrimination of the presence of bile, which appears in clear orange, by image processing. The aim of this experimental study was to evaluate SPECTRA-A ability to detect bile leakage. METHODS: Twelve laparoscopic partial hepatectomies were performed in seven pigs. The common bile duct was clipped distally and dissected, and a catheter was inserted and secured with a suture or a clip. Liver dissection was achieved with an ultrasonic cutting device. Dissection surfaces were checked by frequently switching on the SPECTRA filter to identify the presence of bile leakage. Intraductal ICG injection through the catheter was performed to confirm SPECTRA findings. RESULTS: Three active bile leakages were obtained out of 12 hepatectomies and successfully detected intraoperatively by the SPECTRA. There was complete concordance between NBI and ICG fluorescence detection. No active leaks were found in the remaining cases with both techniques. The leaking area identified was sutured, and SPECTRA was used to assess the success of the repair. CONCLUSIONS: The SPECTRA laparoscopic image processing system allows for rapid detection of bile leaks following hepatectomy without any contrast injection.


Subject(s)
Bile/diagnostic imaging , Hepatectomy/adverse effects , Laparoscopy/methods , Liver Diseases/diagnostic imaging , Narrow Band Imaging/methods , Animals , Common Bile Duct/diagnostic imaging , Disease Models, Animal , Image Processing, Computer-Assisted , Liver Diseases/etiology , Sus scrofa , Swine
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