Learning Curve of Ex Vivo Liver Resection and Autotransplantation in Treating End-Stage Hepatic Alveolar Echinococcosis: A RA-CUSUM Analysis

Background: This retrospective study aimed to evaluate the safety and learning curve of ex vivo liver resection and autotransplantation (ELRA).Methods: A total of 102 consecutive end-stage HAE patients who underwent ELRA between 2014 and 2020 in West China Hospital were enrolled. The primary endpoint was major postoperative complications (comprehensive complication index, CCI > 26). The ELRA learning curve was evaluated using risk-adjusted cumulative sum (RA-CUSUM) methods. The learning phases were determined based on RA-CUSUM analysis and tested for their association with intra- and post-operative endpoints.Results: The median surgery time was 738 (659–818) min, with a median blood loss of 2,250 (1,600–3,000) ml. The overall incidence of major morbidity was 38.24% (39/102). Risk-adjusted cumulative sum analysis demonstrated a learning curve of 53 ELRAs for major postoperative complications. The learning phase showed a significant association with the hemodynamic unstable time (HR −30.29, 95% CI −43.32, −17.25, P < 0.0001), reimplantation time (HR −13.92, 95% CI −23.17, −4.67, P = 0.004), total postoperative stay (HR −6.87, 95% CI −11.33, −2.41, P = 0.0033), and postoperative major morbidity (HR 0.25, 95% CI 0.09, 0.68, p = 0.007) when adjusted for age, disease course, liver function, and remote metastasis.Discussion:Ex vivo liver resection and autotransplantation is feasible and safe with a learning curve of 53 cases for major postoperative complications.

Triphase contrast-enhanced CT to evaluate indications for autologous liver transplantation in patients with end-stage hepatic alveolar echinococcosis

Autologous liver transplantation (ALT) to cure end-stage hepatic alveolar echinococcosis (HAE) requires that hepatobiliary surgeons understand the invasion of intrahepatic structure and adjacent tissues or organs. Triphase contrast-enhanced CT of the liver has been widely used for diagnosis and preoperative evaluation of HAE. Three-dimensional (3D) reconstruction allows for accurate measurement of remnant liver volume (RLV). The objective of the study was to evaluate value of triphase contrast-enhanced CT together with 3D reconstruction in preoperative evaluation of indications for ALT in patients with end-stage HAE. This cohort include twenty-one consecutive patients with end-stage HAE, who preoperatively underwent triphase enhanced CT together with 3D reconstruction for ALT. To depict the indications, the 2D image data were reviewed statistically focusing on porta hepatis invasion, retrohepatic vena cava (RHVC) involvement and degrees of intrahepatic vessel invasion, and the 3D reconstruction was performed to obtain ratio of RLV to standard liver volume (SLV). The results showed that 95.24% patients (20/21) had porta hepatis invasion. When lesions located in right liver lobe, porta hepatis invasion occurred most commonly in the second and third porta hepatis (7/10), whereas the first, second and third porta hepatis were most commonly invaded by lesions in the right and caudate / left medial liver lobes (7/11) (P < 0.05). The mean value of longitudinal invasion of RHVC was 8.0 cm, and 95.2% (20/21) of patients had RHVC invasion with ≥ 180° circumferential invasion. As for the important vascular events, moderate and severe invasion occurred most commonly in the right hepatic vein, right branch of portal vein and RHVC each in 95.2% (20/21) patients (P < 0.05). We also found that preoperative CT had a good agreement with intraoperative findings in assessing intrahepatic vascular involvement by HAE (kappa index = 0.77). The estimated average ratio of RLV to SLV was 0.95 (range, 0.43–1.62). In conclusion, the 2D contrast-enhanced CT could well depict anatomic location and size of HAE, and invasion of porta hepatis and vascular by this disease, and involvement of other adjacent organs and tissues. Above all, 3D reconstruction could accurately measure RLV in patients with end-stage HAE for ALT.

A CT-Based Radiomics Nomogram To Predict The Biological Activity of Hepatic Alveolar Echinococcosis

BackgroundThis study aims to establish a computed tomography (CT) - based radiomics nomogram to predict the biological activity of hepatic alveolar echinococcosis (HAE).MethodsA total of 174 HAE patients (139 for training, 35 for test) were enrolled whose CT and positron emission tomography-computed tomography (PET/CT) examinations were performed before surgery, and the biological activity was evaluated according to the PET/CT. Radiomic features were extracted from CT images, based on which radiomic scores (Rad-score) were calculated with the least absolute shrinkage and selection operator logistic regression. Three radiomics models (K-Nearest Neighbors, Logical regression, and Multilayer Perceptron), including only radiomic features and a radiomics nomogram, comprised of demographics, clinical indexes, and radiomic features were constructed respectively to predict the biological activity of HAE. The model performance was evaluated by area under curve (AUC), decision curve, and calibration curve.Results30 features in total were selected as optimal radiomic features and considered as input to calculate the Rad-score. There were no significant differences in the predictive efficacy between the combined models and the radiomics models from the perspective of the decision curve. The radiomics models was unparalleled, with an AUC of 0.952 (95%CI=0.902~0.981, P<0.0001) and 0.800 (95%CI=0.631~0.916, P<0.0020) in the training and testing cohort, respectively.ConclusionThe radiomics nomogram model showed great potential in identifying HAE biological activity.