No abstract

KRAS mutation is reportedly associated with poor prognosis in patients with different cancer types. However, mutational data on hilar cholangiocarcinoma are few and controversial. The aim of this study was to evaluate the rate of KRAS mutations in a single-center homogeneous population resected for hilar cholangiocarcinoma and the subsequent impact on prognosis. KRAS mutation status was evaluated in 54 patients undergoing major hepatectomy combined with resection of the main biliary confluence and regional lymphadenectomy for hilar cholangiocarcinoma between 2001 and 2019. Among these 54 patients, 12 (22.2%) had a KRAS mutation. KRAS mutation was not related with pathologic characteristics of the tumor. Five-year overall survival (OS) in patients with KRAS mutation was significantly lower than that observed in patients with KRAS wild type (0 vs. 49.2%, respectively; p = 0.003). In the multivariable analysis; independent predictors of poor OS were KRAS mutation (HR = 5.384; p = 0.003) and lymph node metastases (HR = 2.805; p = 0.023). The results of our study suggested that KRAS mutation in hilar cholangiocarcinoma was not rarely observed. KRAS mutation was an independent strong predictor of poor OS. KRAS mutation analysis should be included in the routine pathologic evaluation of resected hilar cholangiocarcinoma in order to better stratify prognosis

Artificial intelligence (AI) is an innovative discipline in medicine, impacting both hepatology and hepato-pancreato-biliary surgery, ensuring reliable outcomes because of its repeatable and efficient algorithms. A considerable number of studies about the efficiency of AI in the management of hepatocellular carcinoma (HCC) have been published. While its diagnostic role is well recognized, providing large amounts of quantitative radiological HCC features, its use in HCC treatment is still debated. Innovative use of AI may help to select the best approach for each patient as it is able to predict the outcomes after resection and/or other treatments. In this review, we assess the role of AI in selecting the best therapeutic option and predicting long-term risks after surgical or interventional treatments for HCC patients. Further studies are needed to consolidate AI applications.

Aim: To define the impact of rapid prototyping for surgical planning in the surgeon’s decision-making process when dealing with a very complex clinical scenario. Method & framework: A straightforward questionnaire involving four simple questions regarding specific technical aspects was administered to the surgeons to evaluate their basic judgments on the surgical strategy to follow. Images from a standard CT scan were used for the subsequent processing and 3D printing of a very cheap anatomical model of a surgical scenario with a low-cost printer, which was shared with the surgeons. At last, the same questionnaire was re-administered to the surgeons. The degree of judgment was found to be modified by approximately 25%. Conclusion: From a surgical point of view, the interaction with technical experts seems to add precious information to the clinical pre-surgical scenario for decision making. Nevertheless, 3D printing was judged too slow for routine adoption.