Comparison of Woven EndoBridge and stent-assisted coiling for treatment of acutely ruptured wide-neck bifurcation aneurysms: Single-center experience.

Objective: Treating wide-necked bifurcation aneurysms (WNBA) is challenging. Nevertheless, recent progress in endovascular techniques is promising. Woven EndoBridge devices (WEB) have exhibited outcomes comparable to conventional treatments like stent-assisted coiling (SAC) in treating aneurysms.

Intra-Arterial Stem Cell Injection for Treating Various Diseases: A New Frontier in Interventional Radiology.

This article provides radiologists with insights into stem cells' functions, sources, and potentially successful clinical treatments via intravascular injection in organs such as the liver, kidney, pancreas, musculoskeletal system, and for ischemic conditions affecting the brain, heart and limbs. Understanding stem cells' significance in interventional radiology and its limitations enables tailored interventions for diverse conditions, ensuring efficient medical care and optimal treatment selection.

Evaluation of MRI proton density fat fraction in hepatic steatosis: a systematic review and meta-analysis.

Background: Amidst the global rise of metabolic dysfunction-associated steatotic liver disease (MASLD), driven by increasing obesity rates, there is a pressing need for precise, non-invasive diagnostic tools. Our research aims to validate MRI Proton Density Fat Fraction (MRI-PDFF) utility, compared to liver biopsy, in grading hepatic steatosis in MASLD.

Methods: A systematic search was conducted across Embase, PubMed/Medline, Scopus, and Web of Science until January 13, 2024, selecting studies that compare MRI-PDFF with liver biopsy for hepatic steatosis grading, defined as grades 0 (< 5% steatosis), 1 (5-33% steatosis), 2 (34-66% steatosis), and 3 (> 66% steatosis).

Methodological insights into ChatGPT's screening performance in systematic reviews.

Background: The screening process for systematic reviews and meta-analyses in medical research is a labor-intensive and time-consuming task. While machine learning and deep learning have been applied to facilitate this process, these methods often require training data and user annotation. This study aims to assess the efficacy of ChatGPT, a large language model based on the Generative Pretrained Transformers (GPT) architecture, in automating the screening process for systematic reviews in radiology without the need for training data.