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Prediction of Radiation Therapy Induced Cardiovascular Toxicity from Pretreatment CT Images in Patients with Thoracic Malignancy via an Optimal Biomarker Approach.
Acad Radiol
January 2025
Medical Image Processing Group, 602 Goddard building, 3710 Hamilton Walk, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 (M.L., M.A., J.K.U., Y.T., C.W., N.P., S.M., D.A.T.). Electronic address:
Rationale And Objectives: Cardiovascular toxicity is a well-known complication of thoracic radiation therapy (RT), leading to increased morbidity and mortality, but existing techniques to predict cardiovascular toxicity have limitations. Predictive biomarkers of cardiovascular toxicity may help to maximize patient outcomes.
Methods: The machine learning optimal biomarker (OBM) method was employed to predict development of cardiotoxicity (based on serial echocardiographic measurements of left ventricular ejection fraction and longitudinal strain) from computed tomography (CT) images in patients with thoracic malignancy undergoing RT.
Epicardial fat tissue, a hidden enemy against the early recovery of left ventricular systolic function after transcatheter aortic valve implantation.
Int J Cardiol Heart Vasc
February 2025
Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands.
Background: Epicardial fat tissue (EFT) is an active organ that can affect cardiac function and structure through endocrine, paracrine, and proinflammatory mechanisms. We hypothesized that greater thickness of EFT may harm the recovery of left ventricular (LV) systolic function in patients with severe aortic stenosis (AS) and reduced LV ejection fraction (EF ≤ 50 %) undergoing transcatheter aortic valve implantation (TAVI).
Methods: A sixty six patients with severe AS and 20 % ≥ LVEF ≤ 50 % who underwent TAVI were included.
Role of Cardiovascular MR Imaging and MR Angiography in Patients with Pulmonary Vascular Disease.
Radiol Clin North Am
March 2025
Radiology Department, Northwestern University Feinberg School of Medicine, Arkes Pavilion, 676 North St Clair Street, Suite 800, Chicago, IL 60611, USA. Electronic address:
Cardiac MR imaging and pulmonary MR angiography (MRA) are important clinical tools for the assessment of pulmonary vascular diseases. There are evolving noncontrast and contrast-enhanced techniques to evaluate pulmonary vasculature. Pulmonary MRA is a feasible imaging alternative to CTA in pulmonary embolism detection.
View Article and Find Full Text PDFHypertrophic Cardiomyopathy: New Clinical and Therapeutic Perspectives of an "Old" Genetic Myocardial Disease.
Genes (Basel)
January 2025
Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padua Medical School, 35128 Padova, Italy.
Since its first pathological description over 65 years ago, hypertrophic cardiomyopathy (HCM), with a worldwide prevalence of 1:500, has emerged as the most common genetically determined cardiac disease. Diagnostic work-up has dramatically improved over the last decades, from clinical suspicion and abnormal electrocardiographic findings to hemodynamic studies, echocardiography, contrast-enhanced cardiac magnetic resonance, and genetic testing. The implementation of screening programs and the use of implantable cardioverter defibrillators (ICDs) for high-risk individuals have notably reduced arrhythmic sudden deaths, altering the disease's mortality profile.
View Article and Find Full Text PDFAutomatic Aortic Valve Extraction Using Deep Learning with Contrast-Enhanced Cardiac CT Images.
J Cardiovasc Dev Dis
December 2024
Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo 060-8638, Japan.
Purpose: This study evaluates the use of deep learning techniques to automatically extract and delineate the aortic valve annulus region from contrast-enhanced cardiac CT images. Two approaches, namely, segmentation and object detection, were compared to determine their accuracy.
Materials And Methods: A dataset of 32 contrast-enhanced cardiac CT scans was analyzed.
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