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Bile Duct Neoplasms

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Machine Learning-Based MRI LAVA Dynamic Enhanced Scanning for the Diagnosis of Hilar Lesions.

Computational and mathematical methods in medicine
OBJECTIVE: To explore the value of machine learning-based magnetic resonance imaging (MRI) liver acceleration volume acquisition (LAVA) dynamic enhanced scanning for diagnosing hilar lesions.

A Multiparametric Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preope...

Robot-Assisted Liver Resection and Cholecystectomy Using Indocyanine-Green for Intrahepatic Cholangiocarcinoma, in a Very Rare Anatomical Anomaly of 'Bipartite Liver'.

Surgical innovation
Robotic hepatobiliary surgery has significantly developed worldwide with substantial clinical results. Hepatobiliary anatomical anomalies increase the complexity of hepatobiliary resection with a relevant risk of iatrogenic lesions. Among congenital ...

Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.

BMC cancer
BACKGROUND: Accurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival...

CT-based deep learning enables early postoperative recurrence prediction for intrahepatic cholangiocarcinoma.

Scientific reports
Preoperatively accurate evaluation of risk for early postoperative recurrence contributes to maximizing the therapeutic success for intrahepatic cholangiocarcinoma (iCCA) patients. This study aimed to investigate the potential of deep learning (DL) a...

A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI.

Current oncology (Toronto, Ont.)
OBJECTIVE: Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepatocellular carcinoma (HCC) based on magnetic resonance imaging (MRI) is crucial for personalized treatment strategy. The purpose of the present study w...

Pure robotic major hepatectomy with biliary reconstruction for hepatobiliary malignancies: first European results.

Surgical endoscopy
BACKGROUND: Combined liver and bile duct resection with biliary reconstruction for hepatobiliary malignancies are defined as highly complex surgical procedures. The robotic platform may overcome some major limitations of conventional laparoscopic sur...

EDLM: Ensemble Deep Learning Model to Detect Mutation for the Early Detection of Cholangiocarcinoma.

Genes
The most common cause of mortality and disability globally right now is cholangiocarcinoma, one of the worst forms of cancer that may affect people. When cholangiocarcinoma develops, the DNA of the bile duct cells is altered. Cholangiocarcinoma claim...

Identification of a novel bile marker clusterin and a public online prediction platform based on deep learning for cholangiocarcinoma.

BMC medicine
BACKGROUND: Cholangiocarcinoma (CCA) is a highly aggressive malignant tumor, and its diagnosis is still a challenge. This study aimed to identify a novel bile marker for CCA diagnosis based on proteomics and establish a diagnostic model with deep lea...