Evaluation of aortic stent endoleaks in the renally impaired patient with ferumoxytol-enhanced MR angiography.

Purpose: To evaluate ferumoxytol-enhanced magnetic resonance angiography (FE-MRA) for assessment of endoleaks in patients with abdominal aortic aneurysms (AAA) and chronic kidney disease (CKD) status post endovascular aneurysm repair (EVAR).

Methods: Of 1854 patients who underwent FE-MRA at a single institution between 03/21/2014 and 08/21/2023, 21 patients with a history of AAA and CKD status post EVAR were retrospectively identified (IRB #13-001341). Multiplanar pre- and post-contrast HASTE, T1-VIBE, and high-resolution breath-held 3D MRA sequences were obtained, where a dose of 4 mg/kg of Ferumoxytol was infused over six minutes.

Evaluation of ChatGPT-Generated Educational Patient Pamphlets for Common Interventional Radiology Procedures.

Rationale And Objectives: This study aimed to evaluate the accuracy and reliability of educational patient pamphlets created by ChatGPT, a large language model, for common interventional radiology (IR) procedures.

Methods And Materials: Twenty frequently performed IR procedures were selected, and five users were tasked to independently request ChatGPT to generate educational patient pamphlets for each procedure using identical commands. Subsequently, two independent radiologists assessed the content, quality, and accuracy of the pamphlets.

ChatGPT in radiology: A systematic review of performance, pitfalls, and future perspectives.

Purpose: The purpose of this study was to systematically review the reported performances of ChatGPT, identify potential limitations, and explore future directions for its integration, optimization, and ethical considerations in radiology applications.

Materials And Methods: After a comprehensive review of PubMed, Web of Science, Embase, and Google Scholar databases, a cohort of published studies was identified up to January 1, 2024, utilizing ChatGPT for clinical radiology applications.

Results: Out of 861 studies derived, 44 studies evaluated the performance of ChatGPT; among these, 37 (37/44; 84.

How AI Responds to Common Lung Cancer Questions: ChatGPT vs Google Bard.

Background The recent release of large language models (LLMs) for public use, such as ChatGPT and Google Bard, has opened up a multitude of potential benefits as well as challenges. Purpose To evaluate and compare the accuracy and consistency of responses generated by publicly available ChatGPT-3.5 and Google Bard to non-expert questions related to lung cancer prevention, screening, and terminology commonly used in radiology reports based on the recommendation of Lung Imaging Reporting and Data System (Lung-RADS) v2022 from American College of Radiology and Fleischner society.