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In the evaluation of cardiomyopathies, cardiac computed tomography (CCT) is predominantly used for assessing congenital or acquired coronary artery diseases as a potential etiology underlying the observed myocardial abnormalities. However, its utility is expected to expand. We present a case of an asymptomatic patient with claustrophobia who sought medical attention due to frequent ventricular beats. The resting electrocardiogram revealed repolarization abnormalities characterized by flattened T-waves in the lateral leads and low QRS voltages in the peripheral leads, whereas transthoracic echocardiography was normal. CCT accurately identified hypodense areas indicative of fibrofatty infiltration within the inferolateral and anterior walls of the left ventricle. Furthermore, late iodine contrast-phase imaging revealed subepicardial late enhancement striae in the same regions. These imaging findings were pivotal in establishing a diagnosis of left-dominant arrhythmogenic cardiomyopathy. This clinical vignette underscores the potential of CCT in tissue characterization, particularly when cardiac magnetic resonance imaging is contraindicated or unavailable.
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http://dx.doi.org/10.4103/jcecho.jcecho_33_24 | DOI Listing |
Eur Radiol Exp
September 2025
Center for MR-Research, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland.
Background: Fetal MRI is increasingly used to investigate fetal lung pathologies, and super-resolution (SR) algorithms could be a powerful clinical tool for this assessment. Our goal was to investigate whether SR reconstructions result in an improved agreement in lung volume measurements determined by different raters, also known as inter-rater reliability.
Materials And Methods: In this single-center retrospective study, fetal lung volumes calculated from both SR reconstructions and the original images were analyzed.
Nat Aging
September 2025
Aging Biomarker Consortium (ABC), Beijing, China.
The global surge in the population of people 60 years and older, including that in China, challenges healthcare systems with rising age-related diseases. To address this demographic change, the Aging Biomarker Consortium (ABC) has launched the X-Age Project to develop a comprehensive aging evaluation system tailored to the Chinese population. Our goal is to identify robust biomarkers and construct composite aging clocks that capture biological age, defined as an individual's physiological and molecular state, across diverse Chinese cohorts.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
Department of Mechanical Engineering, Koc University, Rumeli Feneri Campus, Sarıyer, 34450, Istanbul, Turkey.
Purpose: The design and development of ventricular assist devices have heavily relied on computational tools, particularly computational fluid dynamics (CFD), since the early 2000s. However, traditional CFD-based optimization requires costly trial-and-error approaches involving multiple design cycles. This study aims to propose a more efficient VAD design and optimization framework that overcomes these limitations.
View Article and Find Full Text PDFMed Eng Phys
October 2025
Departament of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering (DEEB/FEEC), University of Campinas (UNICAMP), Campinas, SP, Brazil; National Laboratory for Study of Cell Calcium (LabNECC), Center for Biomedical Engineering (CEB), UNICAMP, Campinas, SP, Brazil.
High-intensity, external electric fields (HIEF) have been used in research and therapy for abnormal generation/propagation of the cardiac electrical activity (e.g., defibrillation), and for promoting access of membrane-impermeant molecules into the cytosol through electropores.
View Article and Find Full Text PDFInt J Med Inform
September 2025
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. Electronic address:
Background: Identifying patient-specific barriers to statin therapy, such as intolerance or deferral, from clinical notes is a major challenge for improving cardiovascular care. Automating this process could enable targeted interventions and improve clinical decision support (CDS).
Objective: To develop and evaluate a novel hybrid artificial intelligence (AI) framework for accurately and efficiently extracting information on statin therapy barriers from large volumes of clinical notes.