18 F-FDG PET/CT of Intracholecystic Papillary Neoplasm in Cystic Neck and Duct.

We report 18 F-FDG PET/CT appearances of intracholecystic papillary neoplasm (ICPN) in the gallbladder neck and duct of a 74-year-old woman with a history of hepatitis B cirrhosis. The lesion presented with a large and sessile soft mass in the neck and duct of gallbladder with obvious glucose metabolism on PET/CT images, which was confirmed pathologically as ICPN (gastric foveolar type) with high-grade intraepithelial neoplasia. ICPN localized in the gallbladder neck and duct is extremely rare, and is easily misdiagnosed as gallbladder carcinoma.

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.

Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography.

Background: The accurate classification of focal liver lesions (FLLs) is essential to properly guide treatment options and predict prognosis. Dynamic contrast-enhanced computed tomography (DCE-CT) is still the cornerstone in the exact classification of FLLs due to its noninvasive nature, high scanning speed, and high-density resolution. Since their recent development, convolutional neural network-based deep learning techniques has been recognized to have high potential for image recognition tasks.