Preoperative Alfa-Fetoprotein and Fibrinogen Predict Hepatocellular Carcinoma Recurrence After Liver Transplantation Regardless of the Milan Criteria: Model Development with External Validation.

BACKGROUND/AIMS: Patient selection is critically important in improving the outcomes of liver transplantation for hepatocellular carcinoma. The aim of the current study was to identify biochemical measures that could affect patient prognosis after liver transplantation. METHODS: A total of 119 patients receiving liver transplantation for hepatocellular carcinoma were used to construct a model for predicting recurrence. The results were validated using an independent sample of 109 patients from independent hospitals. All subjects in both cohorts met the Hangzhou criteria. RESULTS: Analysis of the discovery cohort revealed an association of recurrence with preoperative fibrinogen and AFP levels. A mathematical model was developed for predicting probability of recurrence within 5 years: Y = logit(P) = -4.595 + 0.824 ×fibrinogen concentration (g/L) + 0.641 × AFP score (1 for AFP<=20ng/ml, 2 for 20 400ng/ml). At a cutoff score of -0.85, the area under the curve (AUC) was 0.819 in predicting recurrence (vs. 0.655 when using the Milan criteria). In the validation cohort, this model had reasonable performance in predicting 5-year overall survival (68.8% vs. 28.1% in using the -0.85 cutoff, p< 0.001) and disease-free survival (65.7% vs. 25.9%, p< 0.001). The sensitivity and specificity were 77.0% and 62.5%, respectively. The AUC of this newly developed model was similar to that with the Milan criteria (0.698 vs. 0.678). Surprisingly, the DFS in patients with score <= -0.85 under this model but not meeting the Milan criteria was similar to that in patients meeting the Milan criteria (53.8% vs. 60.0%, p=0.380). CONCLUSIONS: Preoperative AFP and fibrinogen are useful in predicting recurrence of hepatocellular carcinoma after liver transplantation.

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI preoperatively. METHODS: In total, 405 patients were included. A total of 7302 radiomic features and 17 radiological features were extracted by a radiomics feature extraction package and radiologists, respectively. We developed a XGBoost model based on radiomics features, radiological features and clinical variables and a three-dimensional convolutional neural network (3D-CNN) to predict MVI status. Next, we compared the efficacy of the two models. RESULTS: Of the 405 patients, 220 (54.3%) were MVI positive, and 185 (45.7%) were MVI negative. The areas under the receiver operating characteristic curves (AUROCs) of the Radiomics-Radiological-Clinical (RRC) Model and 3D-CNN Model in the training set were 0.952 (95% confidence interval (CI) 0.923-0.973) and 0.980 (95% CI 0.959-0.993), respectively (p = 0.14). The AUROCs of the RRC Model and 3D-CNN Model in the validation set were 0.887 (95% CI 0.797-0.947) and 0.906 (95% CI 0.821-0.960), respectively (p = 0.83). Based on the MVI status predicted by the RRC and 3D-CNN Models, the mean recurrence-free survival (RFS) was significantly better in the predicted MVI-negative group than that in the predicted MVI-positive group (RRC Model: 69.95 vs. 24.80 months, p < 0.001; 3D-CNN Model: 64.06 vs. 31.05 months, p = 0.027). CONCLUSION: The RRC Model and 3D-CNN models showed considerable efficacy in identifying MVI preoperatively. These machine learning models may facilitate decision-making in HCC treatment but requires further validation.

Feasibility of laparoscopic isolated caudate lobe resection for rare hepatic mesenchymal neoplasms.

BACKGROUND: Mesenchymal tumors such as perivascular epithelioid cell neoplasm (PEComa) and inflammatory pseudotumor-like follicular dendritic cell sarcoma (IPT-like FDC sarcoma) are relatively uncommon in the liver and are particularly rare in the caudate lobe. The clinical manifestations and available imaging tests lack specificity for hepatic mesenchymal tumors. To the best of our knowledge, no caudate PEComa or IPT-like FDC sarcoma has been completely resected by laparoscopy. The standard laparoscopic technique, surgical approaches, and tumor margins for potentially malignant or malignant caudate mesenchymal tumors are still being explored. AIM: To assess both the safety and feasibility of laparoscopic resection for rare caudate mesenchymal neoplasms. METHODS: Eleven patients who underwent isolated caudate lobe resection from 2003 to 2017 were identified from a prospective database. Three consecutive patients with rare caudate mesenchymal tumors underwent laparoscopic resection. Patient demographic data, intraoperative parameters, and postoperative outcomes were assessed and compared with the open surgery group. RESULTS: All procedures for the three resection patients with caudate mesenchymal tumors were completed using a total laparoscopic technique by two different approaches. The average operative time was 226 min, and the estimated blood loss was 133 mL. The average length of postoperative hospital stay was 6.3 ± 0.3 d for the laparoscopy group and 15.5 ± 2.3 d for the open surgery group (P < 0.05). There were no perioperative complications or patient deaths in this series. CONCLUSION: Laparoscopic isolated caudate lobe resection for rare mesenchymal neoplasms is a feasible and curative surgical option in selected patients.