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Evaluation of endothelialization of an occluder device with cardiac computed tomography and assessment of the pathological validation.

PLoS One

January 2025

Department of Structural Heart Disease, Cardiovascular Institute and Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Background: Assessing the endothelialization of occlusive devices noninvasively remains a challenge. Cardiac computed tomography angiography (CTA) can be employed to evaluate device endothelialization based on contrast uptake within the occluder.

Objective: This study examined device endothelialization using cardiac CTA and investigated the pathological associations.

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Preterm births constitute a major public health issue and a chronic, cross-generational condition globally. Psychological and biological factors interact in a way that women from low socio-economic status (SES) are disproportionally affected by preterm delivery and at increased risk for the development of perinatal mental health problems. Low SES constitutes one of the most evident contributors to poor neurodevelopment of preterm infants.

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Aims: To investigate the distribution of left atrioventricular coupling index (LACI) among patients with heart failure and left ventricular ejection fraction (LVEF)<50% and to explore its association with the combined endpoint of all-cause death or HF hospitalization at long term follow-up.

Methods And Results: Patients with HF and LVEF<50% undergoing cardiac magnetic resonance (CMR) were evaluated. Patients with atrial fibrillation or flutter were excluded.

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Background: Cardiac magnetic resonance (CMR) is essential for diagnosing cardiomyopathy, serving as the gold standard for assessing heart chamber volumes and tissue characterization. Hemodynamic forces (HDF) analysis, a novel approach using standard cine CMR images, estimates energy exchange between the left ventricular (LV) wall and blood. While prior research has focused on peak or mean longitudinal HDF values, this study aims to investigate whether unsupervised clustering of HDF curves can identify clinically significant patterns and stratify cardiovascular risk in non-ischemic LV cardiomyopathy (NILVC).

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