Coronary Artery Disease Diagnosis; Ranking the Significant Features Using Random Trees Model
University of Birjand（比尔詹德大学）；Maragheh Faculty of Medical Sciences（马拉盖医科大学）；Queensland University of Technology（昆士兰科技大学）；Bauhaus Universität-Weimar（魏玛包豪斯大学）；Obuda University（奥布达大学）；Duy Tan University（越南大智大学）；Ton Duc Thang University（东德大学）
Javad Hassannataj Joloudari, Edris Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Seyyed Mohammad Razavi, Amir Mosavi, Narjes Nabipour, Shahaboddi… 展开作者
Javad Hassannataj Joloudari, Edris Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Seyyed Mohammad Razavi, Amir Mosavi, Narjes Nabipour, Shahaboddin Shamshirband, Laszlo Nadai
备注：
25 pages, 9 figures
发表信息：
International Journal of Environmental Research and Public Health, 2020
Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, the coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagnosing CAD is the use of medical imaging, e.g., angiography. However, angiography is known for being costly and also associated with a number of side effects. Hence, the purpose of this study is to increase the accuracy of coronary heart disease diagnosis through selecting significant predictive features in order of their ranking. In this study, we propose an integrated method using machine learning. The machine learning methods of random trees (RTs), decision tree of C5.0, support vector machine (SVM), decision tree of Chi-squared automatic interaction detection (CHAID) are used in this study. The proposed method shows promising results and the study confirms that RTs model outperforms other models.
The Anatomy of Coronary Risk: How Artery Geometry Shapes Coronary Artery Disease through Blood Flow Haemodynamics -- Latest Methods, Insights and Clinical Implications
In this study OpenFOAM 4.4.2 was used to investigate flow inside the coronary artery of the heart. This step is the first step of our future project, which is to include conjugate heat transfer of the heart with three main coronary arteries. Three different velocities were used as inlet boundary conditions to see the effect of velocity increase on velocity, pressure, and wall shear of coronary artery. Also, three different fluids namely the University of Wisconsin solution, Gelatin, and blood was used to investigate the effect of different fluids on flow inside coronary artery. A code based on…
In recent years, coronary artery disease is escalating and is likely to assume an epidemic proportion by 2030. Currently the reliable methods for detection of coronary arterial lesions are either conventional coronary angiogram (CAG) or MDCT (Multiple Detector Computed Tomography) coronary angiogram. Conventional CAG is an invasive procedure. Conventional CAG and CT (Computed Tomography) angiogram, both require expert supervision of either an interventional cardiologist or a radiologist. In this work, we have proposed a novel design and method for non-invasive detection and localization of cor…
Robust and homogeneous lipid suppression is mandatory for coronary magnetic resonance angiography (MRA) since coronary arteries are commonly embedded in fat. However, effective large volume lipid suppression becomes challenging when performing radial whole-heart coronary MRA and the problem may even be exacerbated at increasing magnetic field strengths. Incomplete fat suppression also generates artifacts, and may affect advanced motion correction methods. The aim was to evaluate a recently reported lipid insensitive MRI method for self-navigated coronary MRA at 3T. Lipid insensitive binomial o…
Nara Institute of Science and Technology（奈良先端科学技术大学院大学）；Technische Universität München（慕尼黑工业大学）；National Cerebral and Cardiovascular Center（国立循环器病研究中心）
Purpose: The motion of the common carotid artery tissue layers along the vessel axis during the cardiac cycle, observed in ultrasound imaging, is associated with the presence of established cardiovascular risk factors. However, the vast majority of the methods are based on the tracking of a single point, thus failing to capture the overall motion of the entire arterial wall. The aim of this work is to introduce a motion tracking framework able to simultaneously extract the trajectory of a large collection of points spanning the entire exploitable width of the image. Method: The longitudinal mo…
We consider an optimal flow control problem in a patient-specific coronary artery bypass graft with the aim of matching the blood flow velocity with given measurements as the Reynolds number varies in a physiological range. Blood flow is modelled with the steady incompressible Navier-Stokes equations. The geometry consists in a stenosed left anterior descending artery where a single bypass is performed with the right internal thoracic artery. The control variable is the unknown value of the normal stress at the outlet boundary, which is need for a correct set-up of the outlet boundary conditio…
Assessing Left Main Bifurcation Anatomy and Haemodynamics: A Potential Surrogate for Disease Risk in Suspected Coronary Artery Disease Without Stenosis?
Fluid-structure interaction simulations for the prediction of fractional flow reserve in pediatric patients with anomalous aortic origin of a coronary artery
Background. Percutaneous coronary intervention(PCI) in stable coronary artery disease(CAD) is commonly triggered by abnormal myocardial perfusion imaging(MPI). However, due to the possibilities of multivessel disease and variability of coronary artery perfusion distribution, opportunity exists to better align anatomic stenosis with perfusion abnormalities to improve revascularization decisions. This study aims to develop a 3D multi-modality fusion approach to assist decision-making for PCI. Methods. Coronary arteries from fluoroscopic angiography(FA) were reconstructed into 3D artery anatomy. …
Numerical models are increasingly used for non-invasive diagnosis and treatment planning in coronary artery disease, where service-based technologies have proven successful in identifying hemodynamically significant and hence potentially dangerous vascular anomalies. Despite recent progress towards clinical adoption, many results in the field are still based on a deterministic characterization of blood flow, with no quantitative assessment of the variability of simulation outputs due to uncertainty from multiple sources. In this study, we focus on parameters that are essential to construct acc…
Automated Cardiac Resting Phase Detection Targeted on the Right Coronary Artery
Friedrich-Alexander University Erlangen-Nuremberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）；Siemens Healthcare GmbH（西门子医疗有限公司）；Siemens Medical Solutions USA, Inc.（美国西门子医疗解决方案公司）；Jose Michel Kalaf Research Institute（何塞·米歇尔·卡拉夫研究所）；Diagnostikum Berlin（柏林诊断中心）
Background. Different mechanisms have been proposed to relate atrial fibrillation (AF) and coronary flow impairment, even in absence of relevant coronary artery disease (CAD). However, the underlying hemodynamics remains unclear. Aim of the present work is to computationally explore whether and to what extent ventricular rate during AF affects the coronary perfusion. Methods. AF is simulated at different ventricular rates (50, 70, 90, 110, 130 bpm) through a 0D-1D multiscale validated model, which combines the left heart-arterial tree together with the coronary circulation. Artificially-built …
In this work, we employ the Synthetic Minority Oversampling Technique (SMOTE) to generate instances of the minority class of an imbalanced Coronary Artery Disease dataset. We firstly analyze the public dataset Z -- Alizadeh Sani, a dataset used for non-invasive prediction of CAD. We perform feature selection to exclude attributes unrelated to Coronary Artery Disease risk. The generation of new samples is performed using SMOTE, a technique commonly employed in machine learning tasks. We design Artificial Neural Networks, Decision Trees, and Support Vector Machines to classify both the original …
