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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.
Eur J Radiol
January 2025
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany. Electronic address:
Objectives: Coronary CT angiography (CCTA) is an excellent tool in ruling out coronary artery disease (CAD) but tends to overestimate especially highly calcified plaques. To reduce diagnostic invasive catheter angiographies (ICA), current guidelines recommend CT-FFR to determine the hemodynamic significance of coronary artery stenosis. Photon-Counting Detector CT (PCCT) revolutionized CCTA and may improve CT-FFR analysis in guiding patients.
View Article and Find Full Text PDFPLoS One
January 2025
Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan.
Objectives: The coronary heart disease (CHD) can influence the development of several diseases. The presence of CHD is correlated to a higher incidence of concurrent diabetic retinopathy (DR) in previous study. Herein, we aim to analyze the relationship between the CHD severity and following DR with different severity.
View Article and Find Full Text PDFLangmuir
January 2025
Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, United States.
Nanocarriers have shown significant promise in the diagnosis and treatment of various diseases, utilizing a wide range of biocompatible materials such as metals, inorganic substances, and organic components. Despite diverse design strategies, key physicochemical properties, including hydrodynamic diameter, shape, surface charge, and hydrophilicity/lipophilicity, are crucial for optimizing biodistribution, pharmacokinetics, and therapeutic efficacy. However, these properties are often influenced by drug payload, presenting an ongoing challenge in developing versatile platform technologies for theranostics.
View Article and Find Full Text PDFPLoS 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.
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