The current standard for measuring coronary artery calcification to determine the extent of atherosclerosis is by calculating the Agatston score from computed tomography (CT). However, the Agatston score disregards pixel values less than 130 Hounsfield Units (HU) and calcium regions less than 1 mm. Due to this thresholding, the score is not sensitive to small, weakly attenuating regions of calcium deposition and may not detect nascent micro-calcification.
View Article and Find Full Text PDFThe development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma.
View Article and Find Full Text PDFIn recent years, cardiovascular immuno-imaging by positron emission tomography (PET) has undergone tremendous progress in preclinical settings. Clinically, two approved PET tracers hold great potential for inflammation imaging in cardiovascular patients, namely FDG and DOTATATE. While the former is a widely applied metabolic tracer, DOTATATE is a relatively new PET tracer targeting the somatostatin receptor 2 (SST2).
View Article and Find Full Text PDFBackground And Aims: Electronic cigarette (EC) use is popular among youth, touted as a safer alternative to smoking and promoted as a tool to aid in smoking cessation. EC cardiovascular safety however is not well established. The aim of this study was to examine cardiovascular consequences of EC use by evaluating their effect on the entire atherosclerotic cascade in young adults using noninvasive combined positron emission tomography (PET)/magnetic resonance imaging (MR) and comparing EC use with age matched smokers of traditional cigarettes and nonsmoking controls.
View Article and Find Full Text PDFThe purpose of this study is to review the published literature for the range of radiographic findings present in patients suffering from coronavirus disease 2019 infection. This novel corona virus is currently the cause of a worldwide pandemic. Pulmonary symptoms and signs dominate the clinical picture and radiologists are called upon to evaluate chest radiographs (CXR) and computed tomography (CT) images to assess for infiltrates and to define their extent, distribution and progression.
View Article and Find Full Text PDFBackground: Automated, accurate, objective, and quantitative medical image segmentation has remained a challenging goal in computer science since its inception. This study applies the technique of convolutional neural networks (CNNs) to the task of segmenting carotid arteries to aid in the assessment of pathology.
Aim: To investigate CNN's utility as an ancillary tool for researchers who require accurate segmentation of carotid vessels.
Purpose: F-MRI is gaining widespread interest for cell tracking and quantification of immune and inflammatory cells in vivo. Different fluorinated compounds can be discriminated based on their characteristic MR spectra, allowing in vivo imaging of multiple F compounds simultaneously, so-called multicolor F-MRI. We introduce a method for multicolor F-MRI using an iterative sparse deconvolution method to separate different F compounds and remove chemical shift artifacts arising from multiple resonances.
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