Achievement of tumor-free resection margin with the largest possible remnant liver parenchyma is the major challenge in hepatic surgery. Therefore, perioperative tumor detection, anatomical mapping of liver segments and also nearby structures are vital to improve the short- and long-term surgical outcomes. Over last decades, several real-time methods have been introduced for this purpose. These methods are mostly based on the utilizing of traceable dyes, which are excreted into the biliary tract. With the advances in minimal invasive surgery and video technology, indocyanine green became the most used dye in this manner. It has been demonstrated that using indocyanine green, small liver tumors can be detected, which cannot be identified using conventional intraoperative methods. Based on the literature, the reported sensitivity of tumor detection using indocyanine green is ranging between 98%-100%, while conventional methods could not reach 90% sensitivity. Posthepatectomy bile leakage, as well as in- or outflow distributions due to the potential vascular reconstructions, are some of the most common complications that can occur especially after complex liver surgeries. Beside the abovementioned advantages of indocyanine green, several researchers have also shown the feasibility of indocyanine green to identify the intraoperative bile leaks and any in- or outflow distributions. Nevertheless, laparoscopic assisted liver surgery is technically challenging, mostly because of the restricted degrees of instrument movements, camera instability, and loss of depth perception. In particular, the loss of depth perception and inaccurate object localization can lead to intraoperative complications and a long learning curve. Advances in video technology, namely 4K ultra-high-definition imaging have been developed to reduce perioperative complications and to shorten the learning curve during laparoscopic liver surgery. This is the first prospective study evaluating the impact of indocyanine green imaging during 4K laparoscopic liver surgery on real-time tumor detection and surgical outcomes.
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Tumor localization
Timeframe: One day