Prognostic role of artificial intelligence among patients with hepatocellular cancer: A systematic review

BACKGROUND Prediction of survival after the treatment of hepatocellular carcinoma (HCC) has been widely investigated, yet remains inadequate. The application of artificial intelligence (AI) is emerging as a valid adjunct to traditional statistics due to the ability to process vast amounts of data and find hidden interconnections between variables. AI and deep learning are increasingly employed in several topics of liver cancer research, including diagnosis, pathology, and prognosis. AIM To assess the role of AI in the prediction of survival following HCC treatment. METHODS A web-based literature search was performed according to the Preferred Reporting Items for Systemic Reviews and Meta-Analysis guidelines using the keywords “artificial intelligence”, “deep learning” and “hepatocellular carcinoma” (and synonyms). The specific research question was formulated following the patient (patients with HCC), intervention (evaluation of HCC treatment using AI), comparison (evaluation without using AI), and outcome (patient death and/or tumor recurrence) structure. English language articles were retrieved, screened, and reviewed by the authors. The quality of the papers was assessed using the Risk of Bias In Non-randomized Studies of Interventions tool. Data were extracted and collected in a database. RESULTS Among the 598 articles screened, nine papers met the inclusion criteria, six of which had low-risk rates of bias. Eight articles were published in the last decade; all came from eastern countries. Patient sample size was extremely heterogenous (n = 11-22926). AI methodologies employed included artificial neural networks (ANN) in six studies, as well as support vector machine, artificial plant optimization, and peritumoral radiomics in the remaining three studies. All the studies testing the role of ANN compared the performance of ANN with traditional statistics. Training cohorts were used to train the neural networks that were then applied to validation cohorts. In all cases, the AI models demonstrated superior predictive performance compared with traditional statistics with significantly improved areas under the curve. CONCLUSION AI applied to survival prediction after HCC treatment provided enhanced accuracy compared with conventional linear systems of analysis. Improved transferability and reproducibility will facilitate the widespread use of AI methodologies

The largest western experience on salvage hepatectomy for recurrent hepatocellular carcinoma: propensity score-matched analysis on behalf of He.RC.O.Le.Study Group

Background: We aimed to evaluate, in a large Western cohort, perioperative and long-term oncological outcomes of salvage hepatectomy (SH) for recurrent hepatocellular carcinoma (rHCC) after primary hepatectomy (PH) or locoregional treatments. Methods: Data were collected from the Hepatocarcinoma Recurrence on the Liver Study Group (He.RC.O.Le.S.) Italian Registry. After 1:1 propensity score-matched analysis (PSM), two groups were compared: the PH group (patients submitted to resection for a first HCC) and the SH group (patients resected for intrahepatic rHCC after previous HCC-related treatments). Results: 2689 patients were enrolled. PH included 2339 patients, SH 350. After PSM, 263 patients were selected in each group with major resected nodule median size, intraoperative blood loss and minimally invasive approach significantly lower in the SH group. Long-term outcomes were compared, with no difference in OS and DFS. Univariate and multivariate analyses revealed only microvascular invasion as an independent prognostic factor for OS. Conclusion: SH proved to be equivalent to PH in terms of safety, feasibility and long-term outcomes, consistent with data gathered from East Asia. In the awaiting of reliable treatment-allocating algorithms for rHCC, SH appears to be a suitable alternative in patients fit for surgery, regardless of the previous therapeutic modality implemented

Performance of Comprehensive Complication Index and Clavien-Dindo Complication Scoring System in Liver Surgery for Hepatocellular Carcinoma

Background: We aimed to assess the ability of comprehensive complication index (CCI) and Clavien‐Dindo complication (CDC) scale to predict excessive length of hospital stay (e‐LOS) in patients undergoing liver resection for hepatocellular carcinoma. Methods: Patients were identified from an Italian multi‐institutional database and randomly selected to be included in either a derivation or validation set. Multivariate logistic regression models and ROC curve analysis including either CCI or CDC as predictors of e‐LOS were fitted to compare predictive performance. E‐LOS was defined as a LOS longer than the 75th percentile among patients with at least one complication. Results: A total of 2669 patients were analyzed (1345 for derivation and 1324 for validation). The odds ratio (OR) was 5.590 (95%CI 4.201; 7.438) for CCI and 5.507 (4.152; 7.304) for CDC. The AUC was 0.964 for CCI and 0.893 for CDC in the derivation set and 0.962 vs. 0.890 in the validation set, respectively. In patients with at least two complications, the OR was 2.793 (1.896; 4.115) for CCI and 2.439 (1.666; 3.570) for CDC with an AUC of 0.850 and 0.673, respectively in the derivation cohort. The AUC was 0.806 for CCI and 0.658 for CDC in the validation set. Conclusions: When reporting postoperative morbidity in liver surgery, CCI is a preferable scale

Current status of liver surgery for non-colorectal non-neuroendocrine liver metastases: the NON.LI.MET. Italian Society for Endoscopic Surgery and New Technologies (SICE) and Association of Italian Surgeons in Europe (ACIE) collaborative international survey

Despite the increasing trend in liver resections for non-colorectal non-neuroendocrine liver metastases (NCNNLM), the role of surgery for these liver malignancies is still debated. Registries are an essential, reliable tool for assessing epidemiology, diagnosis, and therapeutic approach in a single hub, especially when data are dispersive and inconclusive, as in our case. The dissemination of this preliminary survey would allow us to understand if the creation of an International Registry is a viable option, while still offering a snapshot on this issue, investigating clinical practices worldwide. The steering committee designed an online questionnaire with Google Forms, which consisted of 37 questions, and was open from October 5th, 2022, to November 30th, 2022. It was disseminated using social media and mailing lists of the Italian Society of Endoscopic Surgery and New Technologies (SICE), the Association of Italian Surgeons in Europe (ACIE), and the Spanish Chapter of the American College of Surgeons (ACS). Overall, 141 surgeons (approximately 18% of the total invitations sent) from 27 countries on four continents participated in the survey. Most respondents worked in general surgery units (62%), performing less than 50 liver resections/year (57%). A multidisciplinary discussion was currently performed to validate surgical indications for NCNNLM in 96% of respondents. The most commonly adopted selection criteria were liver resectability, RECIST criteria, and absence of extrahepatic disease. Primary tumors were generally of gastrointestinal (42%), breast (31%), and pancreaticobiliary origin (13%). The most common interventions were parenchymal-sparing resections (51% of respondents) of metachronous metastases with an open approach. Major post-operative complications (Clavien-Dindo > 2) occurred in up to 20% of the procedures, according to 44% of respondents. A subset analysis of data from high-volume centers (> 100 cases/year) showed lower post-operative complications and better survival. The present survey shows that NCNNLM patients are frequently treated by surgeons in low-volume hospitals for liver surgery. Selection criteria are usually based on common sense. Liver resections are performed mainly with an open approach, possibly carrying a high burden of major post-operative complications. International guidelines and a specific consensus on this field are desirable, as well as strategies for collaboration between high-volume and low-volume centers. The present study can guide the elaboration of a multi-institutional document on the optimal pathway in the management of patients with NCNNLM

Augmented reality (AR) in minimally invasive surgery (MIS) training: where are we now in Italy? The Italian Society of Endoscopic Surgery (SICE) ARMIS survey

Minimally invasive surgery (MIS) is a widespread approach in general surgery. Computer guiding software, such as the augmented reality (AR), the virtual reality (VR) and mixed reality (MR), has been proposed to help surgeons during MIS. This study aims to report these technologies' current knowledge and diffusion during surgical training in Italy. A web-based survey was developed under the aegis of the Italian Society of Endoscopic Surgery (SICE). Two hundred and seventeen medical doctors’ answers were analyzed. Participants were surgeons (138, 63.6%) and residents in surgery (79, 36.4%). The mean knowledge of the role of the VR, AR and MR in surgery was 4.9 ± 2.4 (range 1–10). Most of the participants (122, 56.2%) did not have experience with any proposed technologies. However, although the lack of experience in this field, the answers about the functioning of the technologies were correct in most cases. Most of the participants answered that VR, AR and MR should be used more frequently for the teaching and training and during the clinical activity (170, 80.3%) and that such technologies would make a significant contribution, especially in training (183, 84.3%) and didactic (156, 71.9%). Finally, the main limitations to the diffusion of these technologies were the insufficient knowledge (182, 83.9%) and costs (175, 80.6%). Based on the present study, in Italy, the knowledge and dissemination of these technologies are still limited. Further studies are required to establish the usefulness of AR, VR and MR in surgical training