Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications

Tang, Dalin; Li, Zhiyong; Gijsen, Frank; Giddens, Don P.

doi:10.1186/1475-925x-14-s1-s1

Cited by 8 publications

(6 citation statements)

References 34 publications

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“…CVDs comprise peripheral and coronary artery diseases, cardiac valve disease, cardiac muscle disorder, congenital heart disease to arrhythmias, and ultimately, heart failure [ 2 ]. CVDs are associated with vulnerable atherosclerotic plaques [ 3 ], formed because of increased luminal pressure and shear stress due to arterial stiffening, causing the acceleration of atheroma formation, stimulation of excessive collagen production, and deposition in the arterial wall, leading to atherosclerosis [ 4 , 5 ]. Thus, according to a recent study, the brachial-ankle pulse wave velocity (baPWV), a candidate measure of subclinical atherosclerosis, can independently predict cardiovascular risk, representing a high-priority therapeutic target to ameliorate CVD [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese

Yang

Gao²,

Huang

et al. 2022

BMC Cardiovasc Disord

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Background Few studies examined the relationship between triglyceride/glucose index (TyG index) and atherosclerosis in Japanese adults. Therefore, this study evaluated their relationship, as measured based on the brachial-ankle pulse wave velocity (baPWV) in Japanese adults. Methods A total of 912 participants was selected from the NAGALA (NAFLD in Gifu Area, Longitudinal Analysis) study conducted from 2004 to 2012. The relationship between the TyG index and baPWV was estimated through a logistic model. Subgroup analyses by sex, age, body mass index (BMI), total cholesterol, low-density lipoprotein cholesterol, estimated glomerular filtration rate (eGFR), and fatty liver was performed. The formula for TyG index was ln (½fasting triglyceride level [mg/dL] × fasting plasma glucose level [mg/dL]). Results A linear relationship between TyG and baPWV was discovered after adjusting for underlying confounders. An increased risk of baPWV was observed after adjusting for sex, age, BMI, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, fatty liver, eGFR, and TyG as a continuous variable (adjusted odds ratio [adj OR], 1.57; 95% confidence interval [95% CI], 1.14–2.18). Compared with the TyG index in the first tertile, the probabilities of subjects in the third tertile that developed to baPWV were 1.78-fold higher (adj OR 1.78, 95% CI 1.08–2.95: P for trend 0.024). Moreover, stable associations were observed between the TyG index and baPWV in different variables through subgroup analyses. Conclusions The highest tertile (above 8.57) of the TyG index was positively and linearly related to subclinical atherosclerosis in Japanese adults and may be valuable as a predicted marker.

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Section: Introductionmentioning

confidence: 99%

The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese

Yang

Gao²,

Huang

et al. 2022

BMC Cardiovasc Disord

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“…Cardiovascular system is a complex circulatory system consisting of the heart, arteries and veins [4]. In recent years, due to the significant improvements in computer technology, modeling based on physical principles has become a powerful tool to simulate the hemodynamic properties of cardiovascular system and has been playing an increasingly important role in the diagnosis of cardiovascular diseases and the development of medical devices [5–7].…”

Section: Introductionmentioning

confidence: 99%

A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

Zhou

Hao

et al. 2019

BioMed Eng OnLine

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The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised.

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“…The P300 [19, 20] technique and the steady state visual evoked potential (SSVEP) [4, 21] technique are examples of the selective attention method. For these the user needs to concentrate on external stimuli that flash in succession (P300) or continuously in a certain frequency (SSVEP).…”

Section: Introductionmentioning

confidence: 99%

Hybrid brain–computer interface for biomedical cyber-physical system application using wireless embedded EEG systems

et al. 2017

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BackgroundOne of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities. Electroencephalography (EEG) has been explored as a non-invasive method of providing assistive technology by using brain electrical signals.MethodsThis paper presents a unique prototype of a hybrid brain computer interface (BCI) which senses a combination classification of mental task, steady state visual evoked potential (SSVEP) and eyes closed detection using only two EEG channels. In addition, a microcontroller based head-mounted battery-operated wireless EEG sensor combined with a separate embedded system is used to enhance portability, convenience and cost effectiveness. This experiment has been conducted with five healthy participants and five patients with tetraplegia.ResultsGenerally, the results show comparable classification accuracies between healthy subjects and tetraplegia patients. For the offline artificial neural network classification for the target group of patients with tetraplegia, the hybrid BCI system combines three mental tasks, three SSVEP frequencies and eyes closed, with average classification accuracy at 74% and average information transfer rate (ITR) of the system of 27 bits/min. For the real-time testing of the intentional signal on patients with tetraplegia, the average success rate of detection is 70% and the speed of detection varies from 2 to 4 s.

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Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications

Cited by 8 publications

References 34 publications

The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese

The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese

A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

Hybrid brain–computer interface for biomedical cyber-physical system application using wireless embedded EEG systems

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