How to Predict Recurrence After Resection of Hepatocellular Carcinoma.

Background/aim: Predictors of recurrence following resection of hepatocellular carcinoma (HCC) are not fully established. This study investigated potential risk factors and prognostic scores for this situation.

Patients And Methods: In 297 patients undergoing resection of HCC between 2000 and 2021, risk scores and potential additional risk factors for intrahepatic and extrahepatic recurrence were assessed.

'Golden Ratio Yoshimura' for meta-stable and massively reconfigurable deployment.

Yoshimura origami is a classical folding pattern that has inspired many deployable structure designs. Its applications span from space exploration, kinetic architectures and soft robots to even everyday household items. However, despite its wide usage, Yoshimura has been fixated on a set of design constraints to ensure its flat foldability.

Accelerated 2D radial Look-Locker T1 mapping using a deep learning-based rapid inversion recovery sampling technique.

Efficient abdominal coverage with T1-mapping methods currently available in the clinic is limited by the breath hold period (BHP) and the time needed for T1 recovery. This work develops a T1-mapping framework for efficient abdominal coverage based on rapid T1 recovery curve (T1RC) sampling, slice-selective inversion, optimized slice interleaving, and a convolutional neural network (CNN)-based T1 estimation. The effect of reducing the T1RC sampling was evaluated by comparing T1 estimates from T1RC ranging from 0.