Automated cardiac vortex ring identification and characterization based on Recurrent All-Pairs Field Transforms and Lagrangian Averaged Vorticity Deviation.

Automated identification of cardiac vortices is a formidable task due to the complex nature of blood flow within the heart chambers. This study proposes a novel approach that algorithmically characterizes the identification criteria of these cardiac vortices based on Lagrangian Averaged Vorticity Deviation (LAVD). For this purpose, the Recurrent All-Pairs Field Transforms (RAFT) is employed to assess the optical flow over the Phase Contrast Magnetic Resonance Imaging (PC-MRI), and to construct a continuous blood flow velocity field and reduce errors that arise from the integral process of LAVD. Additionally, Generalized Hough Transform (GHT) is applied for automated depiction of the structure of cardiac vortices. The effectiveness of this method is demonstrated and validated by the computation of the acquired cardiac flow data. The results of this comprehensive visual and analytical study show that the evolution of cardiac vortices can be effectively described and displayed, and the RAFT framework for optical flow can synthesize the in-between PC-MRIs with high accuracy. This allows cardiologists to acquire a deeper understanding of intracardiac hemodynamics and its impact on cardiac functional performance.

The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective.

CONCEPTUAL INTRODUCTION: To introduce the concept of cybernetical intelligence, deep learning, development history, international research, algorithms, and the application of these models in smart medical image analysis and deep medicine are reviewed in this paper. This study also defines the terminologies for cybernetical intelligence, deep medicine, and precision medicine. REVIEW OF METHODS: Through literature research and knowledge reorganization, this review explores the fundamental concepts and practical applications of various deep learning techniques and cybernetical intelligence by conducting extensive literature research and reorganizing existing knowledge in medical imaging and deep medicine. The discussion mainly centers on the applications of classical models in this field and addresses the limitations and challenges of these basic models. EVALUATION AND DISCUSSIONS: In this paper, the more comprehensive overview of the classical structural modules in convolutional neural networks is described in detail from the perspective of cybernetical intelligence in deep medicine. The results and data of major research contents of deep learning are consolidated and summarized. CONCLUSION: There are some problems in machine learning internationally, such as insufficient research techniques, unsystematic research methods, incomplete research depth, and incomplete evaluation research. Some suggestions are given in our review to solve the problems existing in the deep learning models. Cybernetical intelligence has proven to be a valuable and promising avenue for advancing various fields, including deep medicine and personalized medicine.

Nondimensional diabetes indices for accurate diagnosis of diabetic subjects.

OBJECTIVES: Nondimensional indices or numbers can provide a generalized approach for integrating several biological parameters into one Nondimensional Physiological Index (NDPI) that can help characterize an abnormal state associated with a particular physiological system. In this paper, we have presented four Nondimensional Physiological Indices (NDI, DBI, DIN, CGMDI) for the accurate detection of diabetes subjects. METHODOLOGY: The NDI, DBI, and DIN diabetes indices are based on the Glucose-Insulin Regulatory System (GIRS) Model, represented by the governing differential equation of blood glucose concentration response to the glucose input rate. The solutions of this governing differential equation are employed to simulate the clinical data of the Oral Glucose Tolerance Test (OGTT), and thereby evaluate the GIRS model-system parameters, which are distinctly different for the normal and diabetic subjects. Then these GIRS model parameters are combined to form singular nondimensional indices: NDI, DBI, and DIN. When these indices are applied to the OGTT clinical data, we get significantly different values for normal and diabetic subjects. The DIN diabetes index is a more objective index involving extensive clinical studies, incorporating the GIRS model parameters as well as some key clinical-data markers (based on the information gained from the model clinical simulation and parametric identification). We have then developed another CGMDI diabetes index based on the GIRS model, for the assessment of diabetic subjects using the glucose levels measured by wearable continuous glucose monitoring (CGM) devices. CLINICAL STUDY AND RESULTS: For the DIN diabetes index, our clinical study comprised of 47 subjects (26 normal and 21 diabetics). After applying DIN to the OGTT data, a Distribution Plot of DIN was developed, displaying the ranges of DIN for (i) normal (i.e., non-diabetic) subjects with no risk of becoming diabetic, (ii) normal subjects at risk of becoming diabetic, (iii) borderline diabetic subjects who can become normal (with diet control and treatment), and (iv) distinctly diabetic subjects. This distribution plot is shown to distinctly separate normal subjects from diabetic subjects and also from subjects at risk of becoming diabetic. CONCLUSIONS: In this paper, we have developed several NDPIs in the form of novel nondimensional diabetes indices for the accurate detection of diabetes and diagnosis of diabetic subjects. These nondimensional diabetes indices can enable precision medical diagnostics of diabetes, and thereby also help to develop interventional guidelines for lowering glucose levels by means of insulin infusion. The novelty of our proposed CGMDI is that it utilizes the glucose value monitored by the CGM wearable device. In the future, an app can be developed to use the CGM data in the CGMDI to enable precision diabetes detection.

GCW-UNet segmentation of cardiac magnetic resonance images for evaluation of left atrial enlargement.

BACKGROUND AND OBJECTIVE: Left atrial enlargement (LAE) is an anatomical variation of the left atrium and the result of the long-term increase of left atrial pressure. Most of the increase in stress or volume is due to potential cardiovascular disease. Studies have shown that LAE can independently predict the development of clinically significant cardiovascular disease and heart failure. If the left atrial volume is accurately measured, it will be an essential indicator of human health and an essential means for doctors to find patients' potential diseases. We can analyze the dynamic changes in the left atrial structure and analyze left atrial dilation. However, manual segmentation was inefficient and error-prone before the 3D reconstruction of the left atrium. In order to solve this problem, a convolution neural network (CNN) method based on cardiac magnetic resonance image (MRI) is proposed to automatically segment the left atrial region. METHODOLOGY: In this paper, we have proposed and developed a novel U-Net with Gaussian blur and channel weight neural network (GCW-UNet) to automatically segment the left atrial region in the MRI of a patient with LAE. After Gaussian blur, different resolutions of the MRI are obtained. High-resolution MRI clearly shows the detailed features of the left atrium, while low-resolution MRI clearly shows the overall outline of the left atrium, which can solve the problem of more minor MRI features. Adaptive channel weights can enhance the atrial segmentation capability of the network. RESULTS: Compared with the state-of-the-art left atrial segmentation methods, our CNN-based technique results in the segmentation of the left atrium being closer to the manual segmentation by an experienced radiologist. On the test datasets, the mean Dice similarity coefficient reaches 93.57%. CONCLUSION: Firstly, MRI has a small number of imaging artifacts, which results in low segmentation accuracy. Our method successfully solves the problem. Secondly, due to the high similarity between the background (the area outside the left atrium) and the foreground (the left atrium) in MRI, traditional neural networks misclassify the background as the foreground. Our GCW-Unit can address the imbalanced number of pixels between the foreground and background. Finally, after segmenting the left atrium in the MRI by GCW-Unit, we reconstructed the left atrium to model a three-dimensional heart of a patient suffering from LAE. Based on the different time frames of one heartbeat, we could present the dynamics of the left atrial structure during a cardiac cycle. This can better assist in the evaluation of LAE in heart patients.

Automated vortex identification based on Lagrangian averaged vorticity deviation in analysis of blood flow in the atrium from phase contrast MRI.

OBJECTIVE: To present and validate a method for automated identification of the Lagrangian vortices and Eulerian vortices for analyzing flow within the right atrium (RA), from phase contrast magnetic resonance imaging (PC-MRI) data. METHODOLOGY: Our proposed algorithm characterizes the trajectory integral associated with vorticity deviation and the spatial mean of vortex rings, for the Lagrangian averaged vorticity deviation (LAVD) based identification and tracking of vortex rings within the heart chamber. For this purpose, the optical flow concept was adopted to interpolate the time frames between larger discrete frames, to minimize the error caused by constructing a continuous velocity field for the integral process of LAVD. Then the Hough transform was used to automatically extract the vortex regions of interest. The computed flow data within the RA of the participants' hearts was then used to validate the performance of our proposed method. RESULTS: In the paper, illustrations are provided for derived evolution of Euler vortices and Lagrangian vortices of a healthy subject. The visualization results have shown that our proposed method can accurately identify the Euler vortices and Lagrangian vortices, in the context of measuring the vorticity and vortex volume of the vortices within the RA chamber. Then the employment of Hough transform-based automated vortex extraction has improved the robustness and scalability of the LAVD in identifying cardiac vortices. The analytical results have demonstrated that the introduction of the Horn-Schunck optical flow can more accurately synthesize the intermediate PC-MRI to construct a continuous velocity field, compared with other interpolation methods. CONCLUSION: A novel analytical framework has been developed to accurately identify the flow vortices in the RA chamber based on Horn-Schunck optical flow and Hough transform. From the obtained analytical study results, the development and changes of dominant vortices within this cardiac chamber during the cardiac cycle can be acquired. This can provide to cardiologists a deeper understanding of the hemodynamics within the heart chambers.

A Hybrid Approach for Cardiac Blood Flow Vortex Ring Identification Based on Optical Flow and Lagrangian Averaged Vorticity Deviation.

Objective: The measurement of cardiac blood flow vortex characteristics can help to facilitate the analysis of blood flow dynamics that regulates heart function. However, the complexity of cardiac flow along with other physical limitations makes it difficult to adequately identify the dominant vortices in a heart chamber, which play a significant role in regulating the heart function. Although the existing vortex quantification methods can achieve this goal, there are still some shortcomings: such as low precision, and ignoring the center of the vortex without the description of vortex deformation processes. To address these problems, an optical flow Lagrangian averaged vorticity deviation (Optical flow-LAVD) method is proposed. Methodology: We examined the flow within the right atrium (RA) of the participants' hearts, by using a single set of scans pertaining to a slice at two-chamber short-axis orientation. Toward adequate extraction of the vortex ring characteristics, a novel approach driven by the Lagrangian averaged vorticity deviation (LAVD) was implemented and applied to characterize the trajectory integral associated with vorticity deviation and the spatial mean of rings, by using phase-contrast magnetic resonance imaging (PC-MRI) datasets as a case study. To interpolate the time frames between every larger discrete frame and minimize the error caused by constructing a continuous velocity field for the integral process of LAVD, we implemented the optical flow as an interpolator and introduced the backward warping as an intermediate frame synthesis basis, which is then used to generate higher quality continuous velocity fields. Results: Our analytical study results showed that the proposed Optical flow-LAVD method can accurately identify vortex ring and continuous velocity fields, based on optical flow information, for yielding high reconstruction outcomes. Compared with the linear interpolation and phased-based frame interpolation methods, our proposed algorithm can generate more accurate synthesized PC-MRI. Conclusion: This study has developed a novel Optical flow-LAVD model to accurately identify cardiac vortex rings, and minimize the associated errors caused by the construction of a continuous velocity field. Our paper presents a superior vortex characteristics detection method that may potentially aid the understanding of medical experts on the dynamics of blood flow within the heart.

Lagrangian-averaged vorticity deviation of spiraling blood flow in the heart during isovolumic contraction and ejection phases.

The formation of vortex rings in the left ventricular (LV) blood flow is a mechanism for optimized blood transport from the mitral valve inlet to aortic valve outlet, and the vorticity is an important measure of a well-functioning LV. However, due to lack of quantitative methods, the process of defining the boundary of a vortex in the LV and identifying the dominant vortex components has not been studied previously. The Lagrangian-averaged vorticity deviation (LAVD) can enable us to compute the trajectory integral of the normed difference of the vorticity from its spatial mean. Therefore, in this work, we have employed LAVD to identify the Lagrangian vortices and Eulerian vortices for measuring the vortex volume and vorticity in the LV blood flow. We found that during the LV ejection period, the positive (counterclockwise) and negative (clockwise) vorticity of patients are consistently stronger than those of the healthy groups, and the counterclockwise vortex volume of healthy groups (0.84+0.26 ml) is greater than that of patients (0.55+0.28 ml) during the pre-ejection period. Then, during the middle ejection phase, the counterclockwise vortex ring volume of patients (1.89+0.36 ml) exceeds that of healthy groups (1.38+0.43 ml). Finally, during the end-ejection period, the counterclockwise vortex ring volume of healthy subjects (0.61+0.17 ml) is the same as that of patients (0.60+0.19 ml). The results presented in this paper can provide new insights into the blood flow patterns within the LV. It can accurately indicate the role of vortices and vorticity values in intra-LV flow, and portray how cardiomyopathy (and its distorted contractile mechanism) can affect intra-LV flow patterns and mitigate adequate LV outflow.

Left Atrial Remodeling Mechanisms Associated with Atrial Fibrillation.

Heart disease has always been one of the important diseases that endanger health and cause death. Therefore, it is particularly important to understand left atrium reconstruction and atrial fibrillation before heart image processing. The purpose of this paper is to provide an important review of the mechanisms of left atrial remodeling (LAR) associated with atrial fibrillation (AF). LAR refers to the spectrum of pathophysiological changes in (i) atrial structure and physiological function, and (ii) electric, ionic, and molecular milieu of the LA, in response to stresses imposed by conditions such as hypertension, myocardial ischemia, autonomic denervation and congestive heart failure. The main mechanisms of LAR include electrical remodeling, structural remodeling, metabolic remodeling, autonomic remodeling, neurohormones and inflammation, and other influencing factors. LAR is not only the basic mechanism of AF and heart failure, but also the pathophysiological basis of its progression. In clinical practice, AF is the most common persistent arrhythmia, and is believed to be the result of a combination of mechanisms that have triggers and maintenance mechanisms, including spontaneous ectopic pacing and multiple wavelet reentry. While LA electrophysiological, structural, and ultra-structural changes trigger AF, in turn, AF alters the LA electrical and structural properties that promote its maintenance and recurrence. Chronic AF leads to extensive changes in atrial cellular substructures, including loss of myofibrils, accumulation of glycogen, changes in mitochondrial shape and size, fragmentation of sarcoplasmic reticulum, and dispersion of nuclear chromatin. Electrical remodeling and structural remodeling of the atria during AF, involving structural changes and functional impairment of the left atrium, can lead to serious decline in left ventricular function and severe heart failure. Therefore, LAR and AF are inter-activating phenomena, and the resulting complications can cause serious disabling and fatal events. In this paper, we present (i) the mechanisms of LAR, in the form of structural, electrical, metabolic, and neurohormonal changes, and (ii) their interactive roles in initiating and maintaining AF. These in-depth understanding of the atrial remodeling mechanisms can in turn provide useful insights into the treatment of AF and heart failure.

Coronary arteries hemodynamics: effect of arterial geometry on hemodynamic parameters causing atherosclerosis.

Coronary arteries have high curvatures, and hence, flow through them causes disturbed flow patterns, resulting in stenosis and atherosclerosis. This in turn decreases the myocardial flow perfusion, causing myocardial ischemia and infarction. Therefore, in order to understand the mechanisms of these phenomena caused by high curvatures and branching of coronary arteries, we have conducted elaborate hemodynamic analysis for both (i) idealized coronary arteries with geometrical parameters representing realistic curvatures and stenosis and (ii) patient-specific coronary arteries with stenoses. Firstly, in idealized coronary arteries with approximated realistic arterial geometry representative of their curvedness and stenosis, we have computed the hemodynamic parameters of pressure drop, wall shear stress (WSS) and wall pressure gradient (WPG), and their association with the geometrical parameters of curvedness and stenosis. Secondly, we have similarly determined the wall shear stress and wall pressure gradient distributions in four patient-specific curved stenotic right coronary arteries (RCAs), which were reconstructed from medical images of patients diagnosed with atherosclerosis and stenosis; our results show high WSS and WPG regions at the stenoses and inner wall of the arterial curves. This paper provides useful insights into the causative mechanisms of the high incidence of atherosclerosis in coronary arteries. It also provides guidelines for how simulation of blood flow in patient's coronary arteries and determination of the hemodynamic parameters of WSS and WPG can provide a medical assessment of the risk of development of atherosclerosis and plaque formation, leading to myocardial ischemia and infarction. The novelty of our paper is in our showing how in actual coronary arteries (based on their CT imaging) curvilinearity and narrowing complications affect the computed WSS and WPG, associated with risk of atherosclerosis. This is very important for cardiologists to be able to properly take care of their patients and provide remedial measures before coronary complications lead to myocardial infarctions and necessitate stenting or coronary bypass surgery. We want to go one step further and provide clinical application of our research work. For that, we are offering to cardiologists worldwide to carry out hemodynamic analysis of the medically imaged coronary arteries of their patients and compute the values of the hemodynamic parameters of WSS and WPG, so as to provide them an assessment of the risk of atherosclerosis for their patients. Graphical abstract Theme and aims: Coronary arteries have high curvatures, and hence flow through them causes disturbed flow patterns, resulting in stenosis and atherosclerosis. This in turn decreases the myocardial flow perfusion, causing myocardial ischemia and infarction. Therefore, in order to understand the mechanisms of these phenomena caused by high curvatures and branching of coronary arteries, we have conducted elaborate hemodynamic analysis for both (i) idealized coronary arteries with geometrical parameters representing curvatures and stenosis, and (ii) patient-specific coronary arteries with stenoses. Methods and results: Firstly, in idealized coronary arteries with approximated realistic arterial geometry representative of their curvedness and stenosis, we have computed the hemodynamic parameters of pressure drop, wall shear stress (WSS) and wall pressure gradient (WPG), and their association with the geometrical parameters of curvedness and stenosis. Then, we have determined the wall shear stress and wall pressure gradient distributions in four patient-specific curved stenotic right coronary arteries (RCAs), that were reconstructed from medical images of patients diagnosed with atherosclerosis and stenosis, as illustrated in Figure 1, in which the locations of the stenoses are highlighted by arrows. Figure 1: Three-dimensional CT visualization of arteries in patients with suspected coronary disease. The arteries can be seen as a combination of various curved segments with stenoses at unspecific locations highlighted by arrows. Our results show high WSS and WPG regions at the stenoses and inner wall of the arterial curves, as depicted in Figure 2. Therein, the encapsulations show (i) high WSS, and (ii) high WPG regions at the stenosis and inner wall of the arterial curves. Figure 2: WSS and WPG surface plot of realistic arteries (a), (b), (c) and (d), wherein the small squared parts are enlarged to show the detailed localized contour plots at the stenotic regions. Therein, the circular encapsulations show (i) high WSS and (ii) high WPG regions at the stenosis and inner wall of the arterial curves. Conclusion and novelty: This paper provides useful insights into the causative mechanisms of the high incidence of atherosclerosis in coronary arteries. It also provides guidelines for how simulation of blood flow in patient coronary arteries and determination of the hemodynamic parameters of WSS and WPG can provide a medical assessment of the risk of development of atherosclerosis and plaque formation, leading to myocardial ischemia and infarction. The novelty of our paper is our showing how in actual coronary arteries (based on their CT imaging), curvilinearity and narrowing complications affect the computed WSS and WPG associated with risk of atherosclerosis. This is very important for cardiologists to be able to properly take care of their patients and provide remedial measures before coronary complications lead to myocardial infarctions and necessitate stenting or coronary bypass surgery.

Computational evaluation of smoothed particle hydrodynamics for implementing blood flow modelling through CT reconstructed arteries.

Simulation of blood flow in a stenosed artery using Smoothed Particle Hydrodynamics (SPH) is a new research field, which is a particle-based method and different from the traditional continuum modelling technique such as Computational Fluid Dynamics (CFD). Both techniques harness parallel computing to process hemodynamics of cardiovascular structures. The objective of this study is to develop and test a new robust method for comparison of arterial flow velocity contours by SPH with the well-established CFD technique, and the implementation of SPH in computed tomography (CT) reconstructed arteries. The new method was developed based on three-dimensional (3D) straight and curved arterial models of millimeter range with a 25% stenosis in the middle section. In this study, we employed 1,000 to 13,000 particles to study how the number of particles influences SPH versus CFD deviation for blood-flow velocity distribution. Because further increasing the particle density has a diminishing effect on this deviation, we have determined a critical particle density of 1.45 particles/mm2 based on Reynolds number (Re = 200) at the inlet for an arterial flow simulation. Using this critical value of particle density can avoid unnecessarily big computational expenses that have no further effect on simulation accuracy. We have particularly shown that the SPH method has a big potential to be used in the virtual surgery system, such as to simulate the interaction between blood flow and the CT reconstructed vessels, especially those with stenosis or plaque when encountering vasculopathy, and for employing the simulation results output in clinical surgical procedures.

Sequential venous anastomosis design to enhance patency of arterio-venous grafts for hemodialysis.

Arterio-venous grafts (AVGs), the second best option as long-term vascular access for hemodialysis, face major issues of stenosis mainly due to development of intimal hyperplasia at the venous anastomosis which is linked to unfavorable hemodynamic conditions. We have investigated computationally the utility of a coupled sequential venous anastomotic design to replace conventional end-to-side (ETS) venous anastomosis, in order to improve the hemodynamic environment and consequently enhance the patency of AVGs. Two complete vascular access models with the conventional and the proposed venous anastomosis configurations were constructed. Three-dimensional, pulsatile blood flow through the models was simulated, and wall shear stress (WSS)-based hemodynamic parameters were calculated and compared between the two models. Simulation results demonstrated that the proposed anastomotic design provides: (i) a more uniform and smooth flow at the ETS anastomosis, without flow impingement and stagnation point on the artery bed and vortex formation in the heel region of the ETS anastomosis; (ii) more uniform distribution of WSS and substantially lower WSS gradients on the venous wall; and (iii) a spare route for the blood flow to the vein, to avoid re-operation in case of stenosis. The distinctive hemodynamic advantages observed in the proposed anastomotic design can enhance the patency of AVGs.

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrophic post-MI medical condition is most important for aggressive treatment and management. Advanced image processing techniques together with robust classifier using two-dimensional (2D) echocardiograms may aid for automated classification of the extent of infarcted myocardium. Therefore, this paper proposes novel algorithms namely Curvelet Transform (CT) and Local Configuration Pattern (LCP) for an automated detection of normal, moderately infarcted and severely infarcted myocardium using 2D echocardiograms. The methodology extracts the LCP features from CT coefficients of echocardiograms. The obtained features are subjected to Marginal Fisher Analysis (MFA) dimensionality reduction technique followed by fuzzy entropy based ranking method. Different classifiers are used to differentiate ranked features into three classes normal, moderate and severely infarcted based on the extent of damage to myocardium. The developed algorithm has achieved an accuracy of 98.99%, sensitivity of 98.48% and specificity of 100% for Support Vector Machine (SVM) classifier using only six features. Furthermore, we have developed an integrated index called Myocardial Infarction Risk Index (MIRI) to detect the normal, moderately and severely infarcted myocardium using a single number. The proposed system may aid the clinicians in faster identification and quantification of the extent of infarcted myocardium using 2D echocardiogram. This system may also aid in identifying the person at risk of developing heart failure based on the extent of infarcted myocardium.

An integrated index for automated detection of infarcted myocardium from cross-sectional echocardiograms using texton-based features (Part 1).

Cross-sectional view echocardiography is an efficient non-invasive diagnostic tool for characterizing Myocardial Infarction (MI) and stages of expansion leading to heart failure. An automated computer-aided technique of cross-sectional echocardiography feature assessment can aid clinicians in early and more reliable detection of MI patients before subsequent catastrophic post-MI medical conditions. Therefore, this paper proposes a novel Myocardial Infarction Index (MII) to discriminate infarcted and normal myocardium using features extracted from apical cross-sectional views of echocardiograms. The cross-sectional view of normal and MI echocardiography images are represented as textons using Maximum Responses (MR8) filter banks. Fractal Dimension (FD), Higher-Order Statistics (HOS), Hu's moments, Gabor Transform features, Fuzzy Entropy (FEnt), Energy, Local binary Pattern (LBP), Renyi's Entropy (REnt), Shannon's Entropy (ShEnt), and Kapur's Entropy (KEnt) features are extracted from textons. These features are ranked using t-test and fuzzy Max-Relevancy and Min-Redundancy (mRMR) ranking methods. Then, combinations of highly ranked features are used in the formulation and development of an integrated MII. This calculated novel MII is used to accurately and quickly detect infarcted myocardium by using one numerical value. Also, the highly ranked features are subjected to classification using different classifiers for the characterization of normal and MI LV ultrasound images using a minimum number of features. Our current technique is able to characterize MI with an average accuracy of 94.37%, sensitivity of 91.25% and specificity of 97.50% with 8 apical four chambers view features extracted from only single frame per patient making this a more reliable and accurate classification.

Hemodynamic characterization of transient blood flow in right coronary arteries with varying curvature and side-branch bifurcation angles.

Hemodynamics plays a critical role in the development and progression of plaques that are prone to sites of arterial curvatures and branch bifurcations. The occurrence of atherosclerosis at curvatures of coronary arteries and at the bifurcation sites of their branches are of medical importance. In this study, we have employed computer simulation coupled with a parametric analysis to rigorously quantify the transient wall shear stress (WSS) and wall pressure gradient (WPG) in idealized and image-based right coronary artery (RCA) models with side-branches, in order to explore the effects of curvature and bifurcation on blood flow characteristics and its hemodynamic variables. Upon establishing and implementing this parametric analysis framework, it is found that the relatively lower wall shear stress and WPG regions at the curvature and branch bifurcation sites of arteries coincide with the plaques prone points of the three investigated image-based arteries, to thereby confirm the correlation of the fluid mechanical properties with the arterial geometry variation in consistence with the data from existing literatures. Moreover, the average WSS and Pressure drop (from inlet to outlet) are significantly increased with the more complex geometry of realistic arteries in comparison with idealized arterial models. It can hence be concluded that the geometry of curvature and angulation of the side branches has a significant effect on the WSS and WPG in hemodynamics analysis of RCAs and its correlation with atherosclerotic lesions.

Computer-aided diagnosis of Myocardial Infarction using ultrasound images with DWT, GLCM and HOS methods: A comparative study.

Myocardial Infarction (MI) or acute MI (AMI) is one of the leading causes of death worldwide. Precise and timely identification of MI and extent of muscle damage helps in early treatment and reduction in the time taken for further tests. MI diagnosis using 2D echocardiography is prone to inter-/intra-observer variability in the assessment. Therefore, a computerised scheme based on image processing and artificial intelligent techniques can reduce the workload of clinicians and improve the diagnosis accuracy. A Computer-Aided Diagnosis (CAD) of infarcted and normal ultrasound images will be useful for clinicians. In this study, the performance of CAD approach using Discrete Wavelet Transform (DWT), second order statistics calculated from Gray-Level Co-Occurrence Matrix (GLCM) and Higher-Order Spectra (HOS) texture descriptors are compared. The proposed system is validated using 400 MI and 400 normal ultrasound images, obtained from 80 patients with MI and 80 normal subjects. The extracted features are ranked based on t-value and fed to the Support Vector Machine (SVM) classifier to obtain the best performance using minimum number of features. The features extracted from DWT coefficients obtained an accuracy of 99.5%, sensitivity of 99.75% and specificity of 99.25%; GLCM have achieved an accuracy of 85.75%, sensitivity of 90.25% and specificity of 81.25%; and HOS obtained an accuracy of 93.0%, sensitivity of 94.75% and specificity of 91.25%. Among the three techniques presented DWT yielded the highest classification accuracy. Thus, the proposed CAD approach may be used as a complementary tool to assist cardiologists in making a more accurate diagnosis for the presence of MI.

Transient blood flow in elastic coronary arteries with varying degrees of stenosis and dilatations: CFD modelling and parametric study.

In this paper, we have analysed pulsatile flow through partially occluded elastic arteries, to determine the haemodynamic parameters of wall shear stress (WSS), wall pressure gradient and pressure drops (ΔP), contributing to enhanced flow resistance and myocardial ischaemic regions which impair cardiac contractility and cause increased work load on the heart. In summary, it can be observed that stenoses in an artery significantly influence the haemodynamic parameters of wall shear stress and pressure drop in contrast to dilatations case. This deduces that stenosis plays a more critical role in plaque growth and vulnerability in contrast to dilatation, and should be the key element in cardiovascular pathology and diagnosis. Through quantitative analysis of WSS and ΔP, we have provided a clearer insight into the haemodynamics of atherosclerotic arteries. Determination of these parameters can be helpful to cardiologists, because it is directly implicated in the genesis and development of atherosclerosis.

Automated Identification of Infarcted Myocardium Tissue Characterization Using Ultrasound Images: A Review.

Myocardial infarction (MI) or acute myocardial infarction commonly known as heart attack is one of the major causes of cardiac death worldwide. It occurs when the blood supply to the portion of the heart muscle is blocked or stopped causing death of heart muscle cells. Early detection of MI will help to prevent the infarct expansion leading to left ventricle (LV) remodeling and further damage to the cardiac muscles. Timely identification of MI and the extent of LV remodeling are crucial to reduce the time taken for further tests, and save the cost due to early treatment. Echocardiography images are widely used to assess the differential diagnosis of normal and infarcted myocardium. The reading of ultrasound images is subjective due to interobserver variability and may lead to inconclusive findings which may increase the anxiety for patients. Hence, a computer-aided diagnostic (CAD) technique which uses echocardiography images of the heart coupled with pattern recognition algorithms can accurately classify normal and infarcted myocardium images. In this review paper, we have discussed the various components that are used to develop a reliable CAD system.

In vitro measurements of velocity and wall shear stress in a novel sequential anastomotic graft design model under pulsatile flow conditions.

This study documents the superior hemodynamics of a novel coupled sequential anastomoses (SQA) graft design in comparison with the routine conventional end-to-side (ETS) anastomoses in coronary artery bypass grafts (CABG). The flow fields inside three polydimethylsiloxane (PDMS) models of coronary artery bypass grafts, including the coupled SQA graft design, a conventional ETS anastomosis, and a parallel side-to-side (STS) anastomosis, are investigated under pulsatile flow conditions using particle image velocimetry (PIV). The velocity field and distributions of wall shear stress (WSS) in the models are studied and compared with each other. The measurement results and WSS distributions, computed from the near wall velocity gradients reveal that the novel coupled SQA design provides: (i) a uniform and smooth flow at its ETS anastomosis, without any stagnation point on the artery bed and vortex formation in the heel region of the ETS anastomosis within the coronary artery; (ii) more favorable WSS distribution; and (iii) a spare route for the blood flow to the coronary artery, to avoid re-operation in case of re-stenosis in either of the anastomoses. This in vitro investigation complements the previous computational studies of blood flow in this coupled SQA design, and is another necessary step taken toward the clinical application of this novel design. At this point and prior to the clinical adoption of this novel design, in vivo animal trials are warranted, in order to investigate the biological effects and overall performance of this anastomotic configuration in vivo.

Perspective on CFD studies of coronary artery disease lesions and hemodynamics: a review.

Coronary artery disease (CAD) is the most common cardiovascular disease. Early diagnosis of CAD's physiological significance is of utmost importance for guiding individualized risk-tailored treatment strategies. In this paper, we first review the state-of-the-art clinical diagnostic indices to quantify the severity of CAD and the associated invasive and noninvasive imaging technologies in order to quantify the anatomical parameters of diameter stenosis, area stenosis, and hemodynamic indices of coronary flow reserve and fractional flow reserve. With the development of computational technologies and CFD methods, tremendous progress has been made in applying image-based CFD simulation techniques to elucidate the effects of hemodynamics in vascular pathophysiology toward the initialization and progression of CAD. So then, we review the advancements of CFD technologies in patient-specific modeling, involving the development of geometry reconstruction, boundary conditions, and fluid-structure interaction. Next, we review the applications of CFD to stenotic sites, in order to compute their hemodynamic parameters and study the relationship between the hemodynamic conditions and the clinical indices, to thereby assess the amount of viable myocardium and candidacy for percutaneous coronary intervention. Finally, we review the strengths and limitations of current researches of applying CFD to CAD studies.

Coronary artery bypass grafting hemodynamics and anastomosis design: a biomedical engineering review.

In this paper, coronary arterial bypass grafting hemodynamics and anastomosis designs are reviewed. The paper specifically addresses the biomechanical factors for enhancement of the patency of coronary artery bypass grafts (CABGs). Stenosis of distal anastomosis, caused by thrombosis and intimal hyperplasia (IH), is the major cause of failure of CABGs. Strong correlations have been established between the hemodynamics and vessel wall biomechanical factors and the initiation and development of IH and thrombus formation. Accordingly, several investigations have been conducted and numerous anastomotic geometries and devices have been designed to better regulate the blood flow fields and distribution of hemodynamic parameters and biomechanical factors at the distal anastomosis, in order to enhance the patency of CABGs. Enhancement of longevity and patency rate of CABGs can eliminate the need for re-operation and can significantly lower morbidity, and thereby reduces medical costs for patients suffering from coronary stenosis. This invited review focuses on various endeavors made thus far to design a patency-enhancing optimized anastomotic configuration for the distal junction of CABGs.