AIMC Topic: Liver Neoplasms

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Suitability of DNN-based vessel segmentation for SIRT planning.

International journal of computer assisted radiology and surgery
PURPOSE: The segmentation of the hepatic arteries (HA) is essential for state-of-the-art pre-interventional planning of selective internal radiation therapy (SIRT), a treatment option for malignant tumors in the liver. In SIRT a catheter is placed th...

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

European radiology
OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR).

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

European radiology
OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obta...

Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1.

European radiology
OBJECTIVES: To compare liver metastases changes in CT assessed by radiologists using RECIST 1.1 and with aided simultaneous deep learning-based volumetric lesion changes analysis.

Standardization of robotic right liver mobilization.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Since its introduction 2 decades ago, robotics has been increasingly used for resection of benign and malignant liver lesions. The robotic platform seems to preserve minimally invasive approach benefits, overcoming laparoscopy limitations...

MRI-based deep learning model for differentiation of hepatic hemangioma and hepatoblastoma in early infancy.

European journal of pediatrics
UNLABELLED: Hepatic hemangioma (HH) and hepatoblastoma (HBL) are common pediatric liver tumors and present with similar clinical manifestations with limited distinguishing value of serum AFP in early infancy. An accurate differentiation diagnostic to...

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

European radiology
OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver lesions and distinguish hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT.

A multi-modal deep neural network for multi-class liver cancer diagnosis.

Neural networks : the official journal of the International Neural Network Society
Liver disease is a potentially asymptomatic clinical entity that may progress to patient death. This study proposes a multi-modal deep neural network for multi-class malignant liver diagnosis. In parallel with the portal venous computed tomography (C...

Robot-Assisted Transarterial Chemoembolization of Hepatocellular Carcinoma Using a Coaxial Microcatheter Driving Controller-Responder Robot System: Clinical Pilot Study.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To evaluate the feasibility and safety of robot-assisted transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) using a new coaxial microcatheter driving controller-responder robot (CRR) system.