Khalid Mohammed Ali, Michele Saruwatari, Kochai Jawed, Yoseph Kim, Seihoon Park, Seongjun Cha, Bo Ning, R. J. Cha
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Artificial Intelligence-Assisted Laparoscopic Cholecystectomy in a Preclinical Swine Model
Iatrogenic bile duct injury during laparoscopic cholecystectomy has an incidence rate of 1-2%. The small size of the duct, multiple anatomical variations, and inflammatory conditions make it challenging for the surgeon to identify or protect it during dissection. Despite the difficulties and rising concerns about identifying the bile duct during surgeries, surgeons do not have a specific modality to identify the bile duct except intraoperative cholangiography, which disrupts workflows. Here, we present our new study on laparoscopic cholecystectomy using a quasi-real-time artificial intelligence-assisted biliary-specific fluorescence imaging in a swine model in vivo.