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Heart Valve Dynamics
Published in Joseph D. Bronzino, Donald R. Peterson, Biomedical Engineering Fundamentals, 2019
Choon Hwai Yap, Erin Spinner, Muralidhar Padala, and Ajit P. Yoganathan
Tricuspid regurgitation (TR) is dened as the backow of blood from the right ventricle to the right atrium through the TV and occurs in 8-35% of the population (Antunes and Barlow, 2007). Commonly, TR occurs in conjunction with MV regurgitation (Antunes and Barlow, 2007). Clinically, small levels of TR are detected by color Doppler imaging in many normal persons (Bonow et al., 1998) and is le untreated as it is not seen as life threatening. TR is commonly secondary to another disease and not due to changes in the natural structure of the valve and its leaets (King et al., 1984, Matsuyama et al., 2003). Mechanisms of TR include, but are not limited to, changes in preload, aerload, such as in the case of pulmonary hypertension (Abe et al., 1996, Matsuyama et al., 2003), and right ventricular function (Sadeghi et al., 2004, Dreyfus et al., 2005).
Optimization of tricuspid membrane mechanism for effectiveness and leaflet longevity through hemodynamic analysis
Published in Engineering Applications of Computational Fluid Mechanics, 2022
Young Woo Kim, Hyeong Jun Lee, Su-Jin Jung, June-Hong Kim, Joon Sang Lee
Three-leaflet valves, which prevent blood reflux from the right ventricle (RV) to the right atrium, are termed as tricuspid valves (TVs) (Silver et al., 1971; Wafae et al., 1990). Tricuspid regurgitation (TR), also known as the leakage of blood reflux owing to the incomplete closure of the tricuspid valve, is a common TV disease. Studies indicate that TR can have an incidence rate of up to 85%, particularly in aging societies (Rogers & Bolling, 2009; Yoshida et al., 1988; Lavie et al., 1993). However, compared to other valve diseases such as those of the aortic or pulmonary valves, studies on TR are lacking (Lancellotti et al., 2016).
A portable Raspberry Pi-based system for diagnosis of heart valve diseases using automatic segmentation and artificial neural networks
Published in Cogent Engineering, 2020
Abdulkader Joukhadar, Louay Chachati, Mohammed Al-Mohammed, Obada Albasha
Valvular heart disease is caused by either damage or defect in one of the four heart valves, aortic, mitral, tricuspid, or pulmonary. Defects in these valves can be congenital or acquired (Kameswari et al., 2010; Zeng et al., 2016). Treatment of damaged valves may involve medication alone, but often involves surgical valve repair or replacement (insertion of an artificial heart valve) (Amirjani et al., 2014; Cabrera et al., 2017; Rick et al., 2014). Stenosis and regurgitation represent the conditions associated with valvular heart disease. Stenosis describes a narrowing of the valve opening that prevents adequate outflow of blood. Regurgitation describes the valve's inability to prevent backflow of blood as leaflets of the valve fail to close completely. In general, heart valve diseases include eight common classes, namely aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, pulmonary stenosis, pulmonary regurgitation, tricuspid stenosis, and tricuspid regurgitation (Rick et al., 2014; Zeng et al., 2016). Doppler-echocardiography is today well-established tool in the diagnosis of heart valve diseases, but it is expensive. On the other hand, auscultation (analyzing cardiac sounds) is one of the cheap techniques commonly used by physicians for diagnosis. It is simple and effective; however, it needs long-term training and expertise (Singh et al., 2017). Therefore, many studies have been conducted toward designing systems based on the digital analysis of the phonocardiogram (PCG) signal in order to improve the diagnostic accuracy of physicians. In the field of heart valve disease diagnosis, which is based on PCG signals, most of the studies deal with computer-based systems that can only diagnose few valvular heart cases. Systems are devised in (Ahmad, 2011; Grzegorczyk et al., 2016; Hofmann et al., 2016) to interpret the condition of heart valves as normal or abnormal without further classifying the abnormal ones, while in (Emre & Uguz, 2011; Uğuz, 2012), the valvular heart condition is interpreted as one of the three cases (normal, mitral stenosis, pulmonary stenosis). Furthermore (Noman et al., 2018) presents a novel system to diagnose four valvular heart cases (normal, aortic regurgitation, mitral stenosis, mitral regurgitation), whereas in (Safara et al., 2013; Suboh et al., 2008; Suhas et al., 2017), five valvular heart cases (normal, aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation) are diagnosed. In (Kumar et al., 2018), a system is devised to diagnose five heart valve diseases (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, pulmonary stenosis). According to the aforementioned approaches, the maximum number of the diagnosed valvular heart cases is five, not to mention that the diagnosis process is performed by processing a pre-recorded PCG signal, which means these systems cannot clinically examine the patient to provide the diagnosis result as fast as possible.