15,949 research outputs found

    Modelling mitral valvular dynamics–current trend and future directions

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    Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state-of-the-art modelling of the mitral valve, including static and dynamics models, models with fluid-structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed

    A novel method for estimating myocardial strain: assessment of deformation tracking against reference magnetic resonance methods in healthy volunteers

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    We developed a novel method for tracking myocardial deformation using cardiac magnetic resonance (CMR) cine imaging. We hypothesised that circumferential strain using deformation-tracking has comparable diagnostic performance to a validated method (Displacement Encoding with Stimulated Echoes- DENSE) and potentially diagnostically superior to an established cine-strain method (feature-tracking). 81 healthy adults (44.6 ± 17.7 years old, 47% male), without any history of cardiovascular disease, underwent CMR at 1.5T including cine, DENSE, and late gadolinium enhancement in subjects >45 years. Acquisitions were divided into 6 segments, and global and segmental peak circumferential strain were derived and analysed by age and sex. Peak circumferential strain differed between the 3 groups (DENSE: -19.4 ± 4.8 %; deformation-tracking: -16.8 ± 2.4 %; feature-tracking: -28.7 ± 4.8%) (ANOVA with Tukey post-hoc, F-value 279.93, p<0.01). DENSE and deformation-tracking had better reproducibility than feature-tracking. Intra-class correlation co-efficient was >0.90. Larger magnitudes of strain were detected in women using deformation-tracking and DENSE, but not feature-tracking. Compared with a reference method (DENSE), deformation-tracking using cine imaging has similar diagnostic performance for circumferential strain assessment in healthy individuals. Deformation-tracking could potentially obviate the need for bespoke strain sequences, reducing scanning time and is more reproducible than feature-tracking

    Left ventricular systolic function evaluated by strain echocardiography and relationship with mortality in patients with severe sepsis or septic shock. a systematic review and meta-analysis

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    Sepsis-induced myocardial dysfunction is associated with poor outcomes, but traditional measurements of systolic function such as left ventricular ejection fraction (LVEF) do not directly correlate with prognosis. Global longitudinal strain (GLS) utilizing speckle-tracking echocardiography (STE) could be a better marker of intrinsic left ventricular (LV) function, reflecting myocardial deformation rather than displacement and volume changes. We sought to investigate the prognostic value of GLS in patients with sepsis and/or septic shock

    Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches

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    PMCID: PMC3668194SEP was directly funded by the National Institute for Health Research Cardiovascular Biomedical Research Unit at Barts. SN acknowledges support from the Oxford NIHR Biomedical Research Centre and from the Oxford British Heart Foundation Centre of Research Excellence. SP and PL are funded by a BHF Senior Clinical Research fellowship. RC is supported by a BHF Research Chair and acknowledges the support of the Oxford BHF Centre for Research Excellence and the MRC and Wellcome Trust. PMM gratefully acknowledges training fellowships supporting his laboratory from the Wellcome Trust, GlaxoSmithKline and the Medical Research Council
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