Kelvin K. L. Wong

Cardiac Flow Analysis Applied to Phase Contrast Magnetic Resonance Imaging of the Heart

Phase contrast magnetic resonance imaging is performed to produce flow fields of blood in the heart. The aim of this study is to demonstrate the state of change in swirling blood flow within cardiac chambers and to quantify it for clinical analysis. Velocity fields based on the projection of the three dimensional blood flow onto multiple planes are scanned. The flow patterns can be illustrated using streamlines and vector plots to show the blood dynamical behavior at every cardiac phase. Large-scale vortices can be observed in the heart chambers, and we have developed a technique for characterizing their locations and strength. From our results, we are able to acquire an indication of the changes in blood swirls over one cardiac cycle by using temporal vorticity fields of the cardiac flow. This can improve our understanding of blood dynamics within the heart that may have implications in blood circulation efficiency. The results presented in this paper can establish a set of reference data to compare with unusual flow patterns due to cardiac abnormalities. The calibration of other flow-imaging modalities can also be achieved using this well-established velocity-encoding standard.

Cortical and frontal atrophy are associated with cognitive impairment in age-related confluent white-matter lesion

Objective Although age-related confluent white-matter lesion (WML) is an important substrate for cognitive impairment, the mechanisms whereby WML induces cognitive impairment are uncertain. The authors investigated cognitive predictors in patients with confluent WML. Methods Among 100 patients with ischaemic stroke with confluent WML on MRI, the authors assessed executive function and global cognition by the Mattis Dementia Rating Scale—Initiation/Perseveration Subscale (MDRS I/P) and Mini-Mental State Examination (MMSE), respectively. All volumetric measures were corrected for intracranial volume. The authors investigated the association between basic demography, vascular risk factors, APOE status, WML volume, infarct measures (volume, number, location), microbleed number, atrophy measures (global, central, regional) and cognitive performance. The authors also performed Pittsburgh Compound B (PIB) imaging among seven cognitive impaired patients with stroke. Results WML was no longer related to cognitive performance after adding atrophy into regression equations. Multivariate regression models showed that cortical grey matter volume independently accounted for performance on both the MDRS I/P (β=0.241, p=0.045) and MMSE (β=0.243, p=0.032). Models examining frontal subregions revealed that volumes of both left (β=0.424, p<0.001) and right (β=0.219, p=0.045) lateral frontal orbital gyri predicted MDRS I/P, whereas education (β=0.385, p<0.001) and left lateral frontal orbital gyrus (β=0.222, p=0.037) predicted MMSE. Volumes of WML and cognitively relevant brain regions were significantly associated. Seven patients with PIB imaging showed no uptake pattern typical of Alzheimers disease, suggesting a predominantly vascular aetiology for the cognitive impairment and brain changes in these patients. Conclusions Cognitive impairment in patients with confluent WML is mediated by global and frontal cortical atrophy.

Biomechanical investigation of pulsatile flow in a three-dimensional atherosclerotic carotid bifurcation model

It is a well-established fact that atherosclerosis in carotid bifurcation depends on flow parameters such as wall shear stress, flow pulsatility, and blood pressure. However, it is still not clearly verified how atherosclerosis can become aggravated when plaque experiences a high level of shear stress during advance stages of this disease. In this paper, fluid and structural properties in idealistic geometries are analyzed by using fluid-structure interaction (FSI). From our results, the relationship among blood pressure, stenotic compression, and deformation was established. We show that a high level of compression occurs at the stenotic apex, and can potentially be responsible for plaque progression. Moreover, wall shear stress and deformation are significantly affected by the degree of stenosis. Finally, through analysis of the FSI-based simulation results, we can better understand the parameters that influence flow through a stenotic artery and plaque aggravation, and apply the knowledge for the enhancement of clinical research and prediction of treatment outcomes.

Medical imaging and computer-aided flow analysis of a heart with atrial septal defect

Computer-aided magnetic resonance (MR) fluid motion tracking and cardiac vorticity quantification of the right atrial flow is implemented in this study to suggest a new method for the diagnosis of an atrial septal defect (ASD). MR signals of blood moving in a cardiac chamber can be represented as an image and vary in intensity at every consecutive cardiac phase. A method was devised to perform flow analysis using MR imaging without modification of scan mode or protocol that allows velocity encoding. A single vortex or multiple vortices may appear in the cardiac chamber. However, velocity fields in any flow scenario are normally unable to reveal information for a concise analysis; therefore, in addition to velocity maps, vorticity flow maps on which the velocity field is superimposed are presented. Through a case study, the difference in vortex strengths pre- and post-atrial septal occlusion can be examined, and the results can be verified using computational fluid dynamics. Based on this framework, the degree of vortical flow was assessed for the right atrium of a subject with atrial septal defect. A relationship can be established between right atrial vorticity and the ASD. As such, there is clear utility of the developed system in its potential as a prognostic and investigative tool for the quantitative assessment of cardiac abnormalities parallel to examining magnetic resonance images.

Cardiac flow component analysis

In a chamber of the heart, large-scale vortices are shown to exist as the result of the dynamic blood flow and unique morphological changes of the chamber wall. As the cardiovascular flow varies over a cardiac cycle, there is a need for a robust quantification method to analyze its vorticity and circulation. We attempt to measure vortex characteristics by means of two-dimensional vorticity maps and vortex circulation. First, we develop vortex component analysis by segmenting the vortices using an data clustering algorithm before histograms of their vorticity distribution are generated. The next stage is to generate the statistics of the vorticity maps for each phase of the cardiac cycle to allow analysis of the flow. This is followed by evaluating the circulation of each segmented vortex. The proposed approach is dedicated to examining vortices within the human heart chamber. The vorticity field can indicate the strength and number of large-scale vortices in the chamber. We provide the results of the flow analysis after vorticity map segmentation and the statistical properties that characterize the vorticity components. The success of the cardiac measurement and analysis is illustrated by a case study of the right atrium. Our investigation shows that it is possible to utilize a data clustering algorithm to segment vortices after vorticity mapping, and that the vorticity and circulation analysis of a chamber vorticity can provide new insights into the blood flow within the cardiovascular structure.

Theoretical modeling of micro-scale biological phenomena in human coronary arteries

This paper presents a mathematical model of biological structures in relation to coronary arteries with atherosclerosis. A set of equations has been derived to compute blood flow through these transport vessels with variable axial and radial geometries. Three-dimensional reconstructions of diseased arteries from cadavers have shown that atherosclerotic lesions spiral through the artery. The theoretical framework is able to explain the phenomenon of lesion distribution in a helical pattern by examining the structural parameters that affect the flow resistance and wall shear stress. The study is useful for connecting the relationship between the arterial wall geometries and hemodynamics of blood. It provides a simple, elegant and non-invasive method to predict flow properties for geometrically complex pathology at micro-scale levels and with low computational cost.

Discrete element framework for modelling extracellular matrix, deformable cells and subcellular components

This paper presents a framework for modelling biological tissues based on discrete particles. Cell components (e.g. cell membranes, cell cytoskeleton, cell nucleus) and extracellular matrix (e.g. collagen) are represented using collections of particles. Simple particle to particle interaction laws are used to simulate and control complex physical interaction types (e.g. cell-cell adhesion via cadherins, integrin basement membrane attachment, cytoskeletal mechanical properties). Particles may be given the capacity to change their properties and behaviours in response to changes in the cellular microenvironment (e.g., in response to cell-cell signalling or mechanical loadings). Each particle is in effect an ‘agent’, meaning that the agent can sense local environmental information and respond according to pre-determined or stochastic events. The behaviour of the proposed framework is exemplified through several biological problems of ongoing interest. These examples illustrate how the modelling framework allows enormous flexibility for representing the mechanical behaviour of different tissues, and we argue this is a more intuitive approach than perhaps offered by traditional continuum methods. Because of this flexibility, we believe the discrete modelling framework provides an avenue for biologists and bioengineers to explore the behaviour of tissue systems in a computational laboratory.

Surface Roughness Detection of Arteries via Texture Analysis of Ultrasound Images for Early Diagnosis of Atherosclerosis

There is a strong research interest in identifying the surface roughness of the carotid arterial inner wall via texture analysis for early diagnosis of atherosclerosis. The purpose of this study is to assess the efficacy of texture analysis methods for identifying arterial roughness in the early stage of atherosclerosis. Ultrasound images of common carotid arteries of 15 normal mice fed a normal diet and 28 apoE−/− mice fed a high-fat diet were recorded by a high-frequency ultrasound system (Vevo 2100, frequency: 40 MHz). Six different texture feature sets were extracted based on the following methods: first-order statistics, fractal dimension texture analysis, spatial gray level dependence matrix, gray level difference statistics, the neighborhood gray tone difference matrix, and the statistical feature matrix. Statistical analysis indicates that 11 of 19 texture features can be used to distinguish between normal and abnormal groups (p<0.05). When the 11 optimal features were used as inputs to a support vector machine classifier, we achieved over 89% accuracy, 87% sensitivity and 93% specificity. The accuracy, sensitivity and specificity for the k-nearest neighbor classifier were 73%, 75% and 70%, respectively. The results show that it is feasible to identify arterial surface roughness based on texture features extracted from ultrasound images of the carotid arterial wall. This method is shown to be useful for early detection and diagnosis of atherosclerosis.

Medical image diagnostics based on computer-aided flow analysis using magnetic resonance images.

Most of the cardiac abnormalities have an implication on hemodynamics and affect cardiovascular health. Diagnostic imaging modalities such as computed tomography and magnetic resonance imaging provide excellent anatomical information on myocardial structures, but fail to show the cardiac flow and detect heart defects in vivo condition. The computerized technique for fluid motion estimation by pixel intensity tracking based on magnetic resonance signals represents a promising technique for functional assessment of cardiovascular disease, as it can provide functional information of the heart in addition to analysis of its anatomy. Cardiovascular flow characteristics can be measured in both normal controls and patients with cardiac abnormalities such as atrial septal defect, thus, enabling identification of the underlying causes of these flow phenomena. This review paper focuses on an overview of a flow analysis scheme based on computer-aided evaluation of magnetic resonance intensity images, in comparison with other commonly used medical imaging modalities. Details of the proposed technique are provided with validations being conducted at selected abnormal cardiovascular patients. It is expected that this new technique can potentially extend applications for characterizing cardiovascular defects and their hemodynamic behavior.

MEDICAL IMAGING AND PROCESSING METHODS FOR CARDIAC FLOW RECONSTRUCTION

Intra-cardiac blood flow imaging and visualization is challenging due to the processes involved in generating velocity fields of flow within specific chambers of interest. Visual analysis of cardiac flow or wall deformation is crucial for an accurate examination of the heart. Cardiac chamber boundary encapsulation is one of the key implementations for region definition. To provide intelligible results describing flow within the human heart, cardiac chamber segmentation is a pre-requisite so that fluid motion information can be presented within a region of interest defined by the chamber boundary. A technique that is used to establish contouring along the cardiac wall is described mathematically. This article also sets the practical foundation for flow vector synthesis and visualization in the cardiac discipline. We have outlined conceptual development and the construction of flow field based on a three-dimensional Cartesian grid that can give a greater insight into the blood dynamics within the heart. We developed a framework that is able to present both anatomical as well as flow information by overlaying velocity fields over medical images and displaying them in cine-mode. By addressing most of the methods involved from the programming perspective, procedural execution and memory efficiency have been considered. Our implemented system can be used to examine abnormal blood motion behaviour or discover flow phenomena in normal or defective hearts.