Pattern and extent of intrahepatic infiltration of perihilar cholangiocarcinoma - A case-control study based on liver panoramic digital pathology.

BACKGROUND: The extent of intrahepatic infiltration of perihilar cholangiocarcinoma (PHCC) remains unclear. This research aimed to explore the pattern and extent of intrahepatic infiltration of PHCC to guide surgical treatment and pathological research. MATERIALS AND METHODS: This study included 62 patients diagnosed with PHCC who underwent major hepatectomy. A whole-mount digital liver pathology system (WDLPS) for hepatectomy specimens greater than 10 × 10 cm was used to panoramically assess the intrahepatic infiltration extent of PHCC. RESULTS: The distal intrahepatic infiltration (DIHI) and radial liver invasion (RLI) were important parts of intrahepatic infiltration for PHCC explored by WDLPS. The study confirmed that 75.8% of PHCCs had RLI and the infiltration distance in all patients were within 15,000 µm, 62.9% of PHCCs had DIHI greater than 1 cm away from the main tumor in liver parenchyma. The recurrence-free survival rates and overall survival rates of patients with DIHI were poorer than the patients without DIHI (P＜0.0001, P=0.0038). Arterial invasion on the resected side could be an excellent predictor. A total of 105 liver lobes were resected from 62 PHCC patients. The invasion rates of the left lateral, left medial, right anterior, and right posterior lobe of PHCC were 79%, 100, 100%, and 69% respectively. CONCLUSION: The presence of DIHI in most PHCCs was a significant predictor of poor postoperative recurrence and survival. Based on the extent of intrahepatic infiltration, minor hepatectomy was not suitable as the curative surgery for PHCC. Major hepatectomy and liver transplantation were the ideal radical treatment.

Safety and benefit of modified mesohepatectomy in the treatment of bilobar involvement congenital biliary dilatation.

BACKGROUND: The diseased bile duct in bilobar congenital biliary dilatation is extensive and often requires major hepatectomy or liver transplantation associated with a higher risk. We aimed to evaluate the safety and benefit of modified mesohepatectomy, in comparison with trisectionectomy, to treat bilobar congenital biliary dilatation. METHODS: This study included 28 patients with type IV and V bilobar congenital biliary dilatation. An innovative mesohepatectomy comprising the hepatectomy technique beyond the P/U point and bile duct shaping was applied to 14 patients to address the extensively diseased bile duct and difficulty in hepaticojejunostomy. Another 14 patients received trisectionectomy. The perioperative and long-term outcomes of these patients were compared. RESULTS: The ratio of residual liver volume to standard liver volume in the mesohepatectomy group was higher (78.68% vs. 40.90%, p = 0.005), while the resection rate of the liver parenchyma was lower (28.25% vs. 63.97%, p = 0.000), than that in trisectionectomy group. The mesohepatectomy group had a lower severe complication (>Clavein III, 0% vs. 57.70%, p = 0.019) and incidence of posthepatectomy liver failure (7.14% vs. 42.86%, p = 0.038). No significant difference was observed in blood loss and bile leakage (p > 0.05). All the patients in the mesohepatectomy group achieved optimal results in the long-term follow-up. CONCLUSIONS: mesohepatectomy provides an efficient treatment option for bilobar congenital biliary dilatation and can achieve radical resection, retain more liver parenchyma, and reduce the difficulty of hepaticojejunostomy, especially for patients that are not eligible for major hepatectomy and liver transplantation.

Novel 3D morphological characteristics for congenital biliary dilatation diagnosis: a case-control study.

BACKGROUND: Congenital biliary dilatation (CBD) necessitates the timely removal of dilated bile ducts. Accurate differentiation between CBD and secondary biliary dilatation (SBD) is crucial for treatment decisions, and identification of CBD with intrahepatic involvement is vital for surgical planning and supportive care. This study aimed to develop quantitative models based on bile duct morphology to distinguish CBD from SBD and further identify CBD with intrahepatic involvement. MATERIALS AND METHODS: The retrospective study included 131 CBD and 209 SBD patients between December 2014 and December 2021 for model development, internal validation, and testing. A separate cohort of 15 CBD and 34 SBD patients between January 2022 and December 2022 was recruited for temporally-independent validation. Quantitative shape-based (Shape) and diameter-based (Diam) morphological characteristics of bile ducts were extracted to build a CBD diagnosis model to distinguish CBD from SBD and an intrahepatic involvement identification model to classify CBD with/without intrahepatic involvement. The diagnostic performance of the models was compared with that of experienced hepatobiliary surgeons. RESULTS: The CBD diagnosis model using clinical, Shape, and Diam characteristics showed good performance with an AUROC of 0.942 (95% CI: 0.890-0.994), AUPRC of 0.917 (0.855-0.979), accuracy of 0.891, sensitivity of 0.950, and F1-score of 0.864. The model outperformed two experienced surgeons in accuracy, sensitivity, and F1-score. The intrahepatic involvement identification model using clinical, Shape, and Diam characteristics yielded outstanding performance with an AUROC of 0.944 (0.879-1.000), AUPRC of 0.982 (0.947-1.000), accuracy of 0.932, sensitivity of 0.971, and F1-score of 0.957. The models demonstrated generalizable performance on the temporally-independent validation cohort. CONCLUSIONS: This study developed two robust quantitative models for distinguishing CBD from SBD and identifying CBD with intrahepatic involvement, respectively, based on morphological characteristics of the bile ducts, showing great potential in risk stratification and surgical planning of CBD.

Predicting the outcomes of hepatocellular carcinoma downstaging with the use of clinical and radiomics features.

BACKGROUND: Downstaging of hepatocellular carcinoma (HCC) makes it possible for patients beyond the criteria to have the chance of liver transplantation (LT) and improved outcomes. Thus, a procedure to predict the prognosis of the treatment is an urgent requisite. The present study aimed to construct a comprehensive framework with clinical information and radiomics features to accurately predict the prognosis of downstaging treatment. METHODS: Specifically, three-dimensional (3D) tumor segmentation from contrast-enhanced computed tomography (CT) is employed to extract spatial information of the lesions. Then, the radiomics features within the segmented region are calculated. Combining radiomics features and clinical data prompts the development of feature selection to enhance the robustness and generalizability of the model. Finally, we adopt the support vector machine (SVM) algorithm to establish a classification model for predicting HCC downstaging outcomes. RESULTS: Herein, a comparative study was conducted on three different models: a radiomics features-based model (R model), a clinical features-based model (C model), and a joint radiomics clinical features-based model (R-C model). The average accuracy of the three models was 0.712, 0.792, and 0.844, and the average area under the receiver-operating characteristic (AUROC) of the three models was 0.775, 0.804, and 0.877, respectively. CONCLUSIONS: The novel and practical R-C model accurately predicted the downstaging outcomes, which could be utilized to guide the HCC downstaging toward LT treatment.