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Purpose: The Barcelona Clinic Liver Cancer (BCLC) staging schema is widely used for hepatocellular carcinoma (HCC) treatment. In the updated recommendations, HCC BCLC stage B can become candidates for transplantation. In contrast, hepatectomy is currently not recommended., Methods: This systematic review includes a multi-institutional meta-analysis of patient-level data. Survival, postoperative mortality, morbidity and patient selection criteria for liver resection and transplantation in BCLC stage B are explored. All clinical studies reporting HCC patients with BCLC stage B undergoing liver resection or transplantation were included., Results: A total of 31 studies with 3163 patients were included. Patient level data was available for 580 patients from 9 studies (423 after resection and 157 after transplantation). The overall survival following resection was 50 months and recurrence-free survival was 15 months. Overall survival after transplantation was not reached and recurrence-free survival was 45 months. The major complication rate after resection was 0.11 (95%-CI, 0.0-0.17) with the 90-day mortality rate of 0.03 (95%-CI, 0.03-0.08). Child-Pugh A (93%), minor resection (60%), alpha protein level less than 400 (64%) were common in resected patients. Resected patients were mostly outside the Milan criteria (99%) with mean tumour number of 2.9. Studies reporting liver transplantation in BCLC stage B were scarce., Conclusion: Liver resection can be performed safely in selected patients with HCC BCLC stage B, particularly if patients present with preserved liver function. No conclusion can done on liver transplantation due to scarcity of reported studies., (© 2024. The Author(s).)

Background: Artificial intelligence (AI) is becoming more useful as a decision-making and outcomes predictor tool. We have developed AI models to predict surgical complexity and the postoperative course in laparoscopic liver surgery for segments 7 and 8., Methods: We included patients with lesions located in segments 7 and 8 operated by minimally invasive liver surgery from an international multi-institutional database. We have employed AI models to predict surgical complexity and postoperative outcomes. Furthermore, we have applied SHapley Additive exPlanations (SHAP) to make the AI models interpretable. Finally, we analyzed the surgeries not converted to open versus those converted to open., Results: Overall, 585 patients and 22 variables were included. Multi-layer Perceptron (MLP) showed the highest performance for predicting surgery complexity and Random Forest (RF) for predicting postoperative outcomes. SHAP detected that MLP and RF gave the highest relevance to the variables "resection type" and "largest tumor size" for predicting surgery complexity and postoperative outcomes. In addition, we explored between surgeries converted to open and non-converted, finding statistically significant differences in the variables "tumor location," "blood loss," "complications," and "operation time.", Conclusion: We have observed how the application of SHAP allows us to understand the predictions of AI models in surgical complexity and the postoperative outcomes of laparoscopic liver surgery in segments 7 and 8., (© 2024. The Author(s).)