Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1161/CIRCULATIONAHA.108.791210 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Feasibility of very low iodine dose aortoiliac CT angiography using dual-source photon-counting detector CT.
Eur J Radiol
January 2025
Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA. Electronic address:
Purpose: To evaluate the feasibility of aortoiliac CT-Angiography (CTA) using dual-source photon-counting detector (PCD)-CT with minimal iodine dose.
Methods: This IRB-approved, single-center prospective study enrolled patients with indications for aortoiliac CTA from December 2022 to March 2023. All scans were performed using a first-generation dual-source PCD-CT.
Hydrogel coils in intracranial aneurysm treatment: a multicenter, prospective, randomized open-label trial.
J Neurosurg
January 2025
19Division of Medical Statistics, Division of Data Science, Foundation for Biomedical Research and Innovation at Kobe; and.
Objective: Studies have demonstrated the effectiveness of hydrogel-coated coils (HGCs) to achieve the composite endpoint of decreased recanalization rates and greater safety. Herein, the authors aimed to assess the true ability of second-generation HGCs to prevent recanalization.
Methods: This randomized controlled study, the HYBRID (Hydrocoil Versus Bare Platinum Coil in Recanalization Imaging Data) trial, comparing HGCs with bare platinum coils (BPCs), was conducted in 43 Japanese institutions.
Motion-Compensated Multishot Pancreatic Diffusion-Weighted Imaging With Deep Learning-Based Denoising.
Invest Radiol
January 2025
From the Department of Radiology, Stanford University, Stanford, CA (K.W., M.J.M., A.M.L., A.B.S., A.J.H., D.B.E., R.L.B.); Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA (K.W.); GE HealthCare, Houston, TX (X.W.); GE HealthCare, Boston, MA (A.G.); and GE HealthCare, Menlo Park, CA (P.L.).
Objectives: Pancreatic diffusion-weighted imaging (DWI) has numerous clinical applications, but conventional single-shot methods suffer from off resonance-induced artifacts like distortion and blurring while cardiovascular motion-induced phase inconsistency leads to quantitative errors and signal loss, limiting its utility. Multishot DWI (msDWI) offers reduced image distortion and blurring relative to single-shot methods but increases sensitivity to motion artifacts. Motion-compensated diffusion-encoding gradients (MCGs) reduce motion artifacts and could improve motion robustness of msDWI but come with the cost of extended echo time, further reducing signal.
View Article and Find Full Text PDFCharacterizing Cardiac Adipose Tissue in Post-AMI Patients via CT Imaging: A Comparative Cross-sectional Study.
Eur Heart J Cardiovasc Imaging
January 2025
National Heart Center Singapore, Singapore, Singapore.
Aims: To identify differences in CT-derived perivascular (PVAT) and epicardial adipose tissue (EAT) characteristics that may indicate inflammatory status differences between post-treatment acute myocardial infarction (AMI) and stable coronary artery disease (CAD) patients.
Methods And Results: A cohort of 205 post-AMI patients (age 59.8±9.
Artificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study.
PLoS One
January 2025
Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania, Brazil.
This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of improving the diagnosis and treatment of coronary artery disease. The methodology included data collection in a clinical environment, followed by data preparation and analysis using the 3D Slicer Platform for manual segmentation, and subsequently, the application of artificial intelligence models for automated segmentation, focusing on the efficiency of identifying the walls of the left ventricular. A total of 83 clinical routine exams were collected, each exam containing 50 slices, which is 4,150 images.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!