Objective: The clinical aim of this work is to predict intraoperative LRC from preoperative CT scans only. Summary of Background Data: Liver resection (LR) is the most prevalent curative treatment for primary liver cancer, yet overall mortality/morbidity rates remain elevated. The conventional definition and classification of LR complexity (LRC) lack inclusion of the disease-induced 3D anatomical surgery complexity. Methods: 3D models of the organ, tumors and blood vessels were generated from Deep Learning models trained on patients CT scans. The surgeons’ expertise on which anatomical factors lead to LRC was translated into a new anatomical frame of reference around the Hepatic Central Zone (HCZ). A fully automatic pipeline to generate the HCZ and quantify the tumors position relative to it was assessed. An AI model was then trained to predict LRC from a patient cohort for whom LRC was annotated at the end of each surgery. The AI-prediction was finally compared to prediction of surgeons that only saw the patient preoperative CT scan. Results: The 3D reconstructions are successfully evaluated on benchmark datasets. The HCZ is accurately generated for a variety of atypical vascular anatomies (dice score 82±4.6%). The automatic pipeline is successfully run on a 145 HCC patient cohort. The predicted LRC outperforms the surgeons’ individual and combined anticipated complexities (accuracy and AUC scores: 79.4±3.4% and 85.1±3.2% respectively). Conclusion: This automatic digital tool accurately predicts intraoperative LRC and paves the way for an innovative oncology surgery planning. This tool could help orient patients towards appropriate medical centers depending on the predicted LRC level.

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Background/Objectives: The increasing adoption of laparoscopic liver resection (LLR) and changes in clinical management may influence access to curative treatments for patients on the liver transplant waiting list. We aimed to analyze temporal trends in LLR use and to explore the association between the proportion of LLR and the dropout rate from the intention-to-treat (ITT) population. A secondary objective was to assess the risk of dropout or death versus curative treatment (transplantation or resection) in patients with hepatocellular carcinoma (HCC) compared with non-HCC candidates using a competing-risk model. Methods: We performed a retrospective cohort study of all patients listed for liver transplantation between 2015 and 2023. Annual rates of LLR and dropout were calculated, and their correlation was evaluated using Spearman’s rho. The risk of dropout/death and competing curative events (OLT, resection, or thermal ablation) was assessed using Fine–Gray competing-risk regression, adjusted for HCC status. Results: From 2015 to 2023, LLR accounted for a progressively increasing proportion of liver resections. A significant negative correlation was observed between annual LLR rates and dropout rates (ρ = −0.78, p = 0.008), indicating fewer ITT failures with greater LLR adoption. In the competing-risk analysis, HCC patients had a significantly lower subdistribution hazard for dropout/death (SHR 0.27, 95% CI 0.18–0.42, p < 0.001) and a higher probability of receiving a curative treatment (SHR 1.65, 95% CI 1.40–1.94, p < 0.001). Conclusions: The increased use of LLR was associated with improved access to curative therapies and a reduced dropout risk on the liver transplant waiting list. HCC patients showed a more favorable competing-risk profile compared with non-HCC candidates.

Normothermic machine perfusion (NMP) has emerged as a valuable preservation technique in liver transplantation, offering improved graft assessment and viability. Traditionally, liver grafts undergo a second cooling phase before implantation, which may contribute to cellular damage through ischemia-reperfusion injury. In this “How To Do It” article, we describe our surgical technique to avoid re-cooling following NMP. Specifically, after retrieval from the perfusion device, the graft is directly inserted into the surgical field and undergoes a standardized portal flush with 1 L of 5% albumin at room temperature before reperfusion. This method maintains physiological temperature, potentially reducing reperfusion stress and enhancing graft function. We detail step-by-step procedural aspects, including organ handling, vascular anastomoses, and intraoperative considerations, supported by our clinical outcomes. Export

Background: Ischemia/reperfusion injury (IRI), acute rejection (AR), and delayed graft function (DGF) might occur as major complications following kidney transplantation. Thus, the identification of biomarkers for the IRI, AR, and/or DGF development becomes crucial as it may help to guide post-transplant management. Natural killer (NK) cells, hepatic interstitial T-lymphocytes (T-Li), and NK-T cells are crucial in both innate and adaptive immunity after abdominal solid organ transplantation. Hence, the aim of this study was to evaluate the impact of the immune system after graft reperfusion during KT in adults in order to identify predictive biomarkers. Methods: The NK, T-Li, and NK-T phenotypes and concentrations were retrospectively analyzed in a consecutive series of liver perfusates obtained after organ procurement flushing the abdominal cavity recovered from deceased brain donors (DBDs). Their percentage was compared with the renal transplant recipients’ characteristics with kidneys taken from the same DCDs. The hepatic perfusate cells were purified by density gradient centrifugation. Flow cytometric investigation was used to determine their phenotype with the following immunological markers in order to determine the relative percentage of T-Li, NK-T, and NK cells: CD3, CD4, CD8, and CD56. Results: 42 DBDs’ liver perfusates were analyzed. The related clinical outcomes of kidney transplant recipients from 2010 to 2020 performed at our Institute were evaluated. Time in days of delayed functional recovery of transplanted kidneys (DGF) (p = 0.02) and the onset of secondary infection from a cytomegalovirus (p = 0.03) were significantly associated with the T-Li percentage. An increased relative risk (HR) of organ survival was significantly associated with the percent cell concentration of T-Li and time to DGF, on COX analysis, were (HR = 1.038, p = 0.04; and HR = 1.029, p = 0.01, respectively). None relevant clinical outcomes in kidney transplant patients were associated with the specificity of the NK and NK-T cell proportions. Conclusions: A new potential role of T-Li cells was detected in the context of hepatic perfusate from DBDs. It could detect potential impacts in organ allocation, surgical procuring techniques, and in the analysis of IRI pathophysiological events.