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Diffusion of laparoscopic major hepatectomies is experiencing a steady increasing trend, although slower compared to minor resections. The aim of this single-center study is to discuss current trends and indications in the application of minimally invasive techniques to major hepatic resections. Preoperative patients and disease characteristics of 49 laparoscopic major hepatectomies (LPS group), performed between 2005 and 2015, were compared with 585 open hepatectomies (Open group) to analyze differences in patients recruitment. Factors which were found to be differently distributed between groups were used as covariates in a propensity score-based case-matched analysis with a 1:3 ratio between LPS group and 147 patients from the Open group (constituting Open-mat group). Short-term outcome was analyzed in matched groups. ASA score, previous abdominal surgery, previous interventional procedures, indication, lesion size and associated procedures were significantly different between the LPS and the Open group. Short-term outcome analysis revealed that blood loss (200 vs 350 mL, p = 0.044) and time for functional recovery (3 vs 4 days, p = 0.05) were reduced in the LPS compared to the Open-mat group, in spite of longer length of surgery (260 vs 170 min, p = 0.041) and comparable oncological adequacy. Even though data on technical feasibility of laparoscopic major resections and their benefits in terms of blood loss and functional recovery support the diffusion of minimally invasive approach, the limit of the technique is still represented by the reduced pool of suitable candidates.

Hypothermic machine perfusion (HPM) grants a better postoperative outcome in transplantation of organs procured from extended criteria donors (ECDs) and donors after cardiac death (DCD). So far, the only available parameter for outcome prediction concerning those organs is pretransplant biopsy score. The aim of this study is to evaluate whether renal resistance (RR) trend during HPM may be used as a predictive marker for post-transplantation outcome. From December 2015 to present, HMP has been systematically applied to all organs from ECDs and DCD. All grafts underwent pretransplantation biopsy evaluation using Karpinski's histological score. Only organs that reached RR value ≤1.0 within 3 hours of perfusion were transplanted. Single kidney transplantation (SKT) or double kidney transplantation (DKT) were performed according to biopsy score results. Sixty-five HMPs were performed (58 from ECDs and 7 from DCD/ECMO donors). Fifteen kidneys were insufficiently reconditioned (RR > 1) and were therefore discarded. Forty-nine kidneys were transplanted, divided between 21 SKT and 14 DKT. Overall primary nonfunction (PNF) and delayed graft function (DGF) rate were 2.9 and 17.1%, respectively. DGF were more common in kidneys from DCD (67 vs. 7%; P = 0.004). Biopsy score did not correlate with PNF/DGF rate (P = 0.870) and postoperative creatinine trend (P = 0.796). Recipients of kidneys that reached RR ≤ 1.0 within 1 hour of HMP had a lower PNF/DGF rate (11 vs. 44%; P = 0.033) and faster serum creatinine decrease (POD10 creatinine: 1.79 mg/dL vs. 4.33 mg/dL; P = 0.019). RR trend is more predictive of post-transplantation outcome than biopsy score. Hence, RR trend should be taken into account in the pretransplantation evaluation of the organs.

Artificial intelligence makes surgical resection easier and safer, and, at the same time, can improve oncological results. The robotic system fits perfectly with these more or less diffused technologies, and it seems that this benefit is mutual. In liver surgery, robotic systems help surgeons to localize tumors and improve surgical results with well-defined preoperative planning or increased intraoperative detection. Furthermore, they can balance the absence of tactile feedback and help recognize intrahepatic biliary or vascular structures during parenchymal transection. Some of these systems are well known and are already widely diffused in open and laparoscopic hepatectomies, such as indocyanine green fluorescence or ultrasound-guided resections, whereas other tools, such as Augmented Reality, are far from being standardized because of the high complexity and elevated costs. In this paper, we review all the experiences in the literature on the use of artificial intelligence systems in robotic liver resections, describing all their practical applications and their weaknesses.

To determine the accuracy of preoperative imaging, including contrast-enhanced computed tomography (CE-CT), endoscopic ultrasound (EUS), and 68 Gallium-DOTATOC positron emission tomography ( 68 Ga-DOTATOC PET), in identifying nodal metastases (N+) in sporadic nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs). Background: An accurate preoperative identification of N+ in NF-PanNETs is critical for surgical planning. The accuracy of different imaging techniques in detecting lymph node (LN) metastases in NF-PanNETs has been poorly investigated. Methods: All consecutive patients undergoing surgery for sporadic NF-PanNETs (2018 were enrolled in a prospective study (DETECTYON; NCT03918759). The accuracy of preoperative imaging techniques in detecting N+ was assessed through sensitivity, specificity positive and negative predictive values. Results: Overall, 100 patients with NF-PanNETs underwent CE-CT, EUS, and 68 Ga-DOTATOC PET before pancreatic resection. LN metastases were found in 42 cases (42%). Sensitivity, specificity, positive predictive value, and negative predictive value of different imaging techniques were 26%, 95%, 79%, 64% for CE-CT, 19%, 98%, 89%, 63% for EUS, and 12%, 95%, 63%, 60% for 68 Ga-DOTATOC PET, respectively. Radiologic tumor size > 4 cm and the presence of radiologic N+ at ≥ 1 imaging were independent predictors of N+ at pathology. The identification of N+ at ≥ 1 imaging technique was associated with a higher number of positive LNs compared with negative imaging (4 vs 2) (P = 0.012). Conclusions: CE-CT, EUS, and 68 Ga-DOTATOC PET are poorly sensitive in predicting nodal status in NF-PanNETs despite a high specificity.

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