Predicting future myocardial infarction from angiographies with deep learning

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Atherosclerosis is a lipid driven chronic inflammatory disease that is characterized by the formation of plaques at predilection sites. These predilection sites (side branches, curved segments, and bifurcations) have often been associated with disturbed sh ...

Coronary artery disease, caused by the buildup of atherosclerotic plaques in the coronary vessel wall, is one of the leading causes of death in the world. For high-risk patients, coronary artery bypass graft is the preferred treatment. Despite overall exce ...

Introduction: Imaging studies are used to guide patient selection for acute stroke treatment. Perfusion CT (pCT) is widely used to identify the acute ischemic core and penumbra, but the prediction of the final infarct remains challenging. With the advent o ...

Coronary artery disease is one of the leading causes of death worldwide. The stenotic coronary vessels are generally treated with coronary artery bypass grafts (CABGs), which can be either arterial (internal mammary artery, radial artery) or venous (saphen ...

A fast computational framework is devised to the study of several configurations of patient-specific coronary artery bypass grafts. This is especially useful to perform a sensitivity analysis of the hemodynamics for different flow conditions occurring in n ...

Background NCOR1 (nuclear receptor corepressor 1) is an essential coregulator of gene transcription. It has been shown that NCOR1 in macrophages plays important roles in metabolic regulation. However, the function of macrophage NCOR1 in response to myocard ...

Photodynamic therapy (PDT), which is based on the activation of photosensitizers with light, can be used to reduce plaque burden. We hypothesized that intra-arterial photosensitizer administration and photo-activation will lead to high and rapid accumulati ...

Despite the improving imaging techniques, it remains challenging to produce magnetic resonance (MR) imaging fingerprints depicting severity of acute ischemia. The aim of this study was to evaluate the potential of the overall high-field H-1 MR Spectroscopy ...

Background Impaired heart rate variability (HRV) is associated with increased mortality in sinus rhythm. However, HRV has not been systematically assessed in patients with atrial fibrillation (AF). We hypothesized that parameters of HRV may be predictive o ...

In this work a reduced-order computational framework for the study of haemodynamics in three-dimensional patient-specific configurations of coronary artery bypass grafts dealing with a wide range of scenarios is proposed. We combine several efficient algor ...

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

Developing algorithmic approaches for the rational design and discovery of materials can enable us to systematically find novel materials, which can have huge technological and social impact. However, such rational design requires a holistic perspective ov ...

Coronary artery disease, the main cause of heart disease, develops as immune cells and lipids accumulate into plaques within the coronary arterial wall. As a plaque grows, the tissue layer (fibrous cap) separating it from the blood flow becomes thinner and ...

BackgroundCoronary atherothrombosis due to atherosclerotic plaque rupture or erosion is frequently associated with acute coronary syndromes (ACS). Significant efforts have been made to elucidate the pathophysiological mechanisms underlying acute coronary e ...

Hyperpolarized carbon-13 magnetic resonance spectroscopy ((13)C MRS) enables the sensitive and noninvasive assessment of the metabolic changes occurring during myocardial ischemia-reperfusion. Ischemia-reperfusion models using hyperpolarized (13)C MRS are ...

Predicting future myocardial infarction from angiographies with deep learning

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Considerations for analysis of endothelial shear stress and strain in FSI models of atherosclerosis

Computational study of the risk of restenosis in coronary bypasses

Deep Learning Building on Prior Ischemic Core Segmentation Improves Prediction of Infarction After Stroke

A computational fluid-structure interaction analysis of coronary Y-grafts

Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts

Macrophage NCOR1 Deficiency Ameliorates Myocardial Infarction and Neointimal Hyperplasia in Mice

Intra-Arterial Drug and Light Delivery for Photodynamic Therapy Using Visudyne (R): Implication for Atherosclerotic Plaque Treatment

Metabolic fingerprints discriminating severity of acute ischemia using in vivo high-field H-1 magnetic resonance spectroscopy

Heart Rate Variability Triangular Index as a Predictor of Cardiovascular Mortality in Patients With Atrial Fibrillation

Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

The Role of Machine Learning in the Understanding and Design of Materials

Ultrafast laser ablation for targeted atherosclerotic plaque removal

Update on the role of angiotensin in the pathophysiology of coronary atherothrombosis

An Intact Small Animal Model of Myocardial Ischemia-Reperfusion: Characterization of Metabolic Changes by Hyperpolarized 13C MR Spectroscopy