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Analysis of strain in the human left ventricle using real-time 3D echocardiography and optical flow
Cardiovascular disease (CVD) consistently ranks among the leading causes of death in the United States. The most common subtype of CVD, ischemic heart disease, is a frequent precursor of myocardial infarction and heart failure, most commonly affecting the left ventricle (LV). Today, echocardiography is regarded as the gold standard in screening, diagnosis, and monitoring of LV dysfunction. But while global assessment of LV function tends to be quantitative, cardiologists with specific expertise still perform many regional evaluations subjectively. However, a more objective and quantitative measure of regional function – myocardial strain – has been developed and widely studied using 2D echocardiography.
With recent developments in real-time 3D echocardiography (RT3DE), it has become possible to measure strain in its native 3D orientation as well. Our laboratory’s earlier work introduced the Optical Flow (OF) method of strain analysis, which was validated on simulated echocardiograms as well as through animal studies. The principal goal of this thesis is to translate this OF-based method of strain estimation from the research setting to the patient’s bedside.
We have performed a series of studies to evaluate the feasibility, accuracy, and reproducibility of OF-based myocardial strain estimation in a routine clinical setting. The first investigation focused on the optimization of RT3DE acquisition and the OF processing pipeline for use in human subjects. Subsequently, we evaluated the capacity of this technique to distinguish abnormal strain patterns in patients with CVD and varying degrees of LV dysfunction. Our analysis revealed that segmental strain measures obtained by OF may have better sensitivity and specificity than the more commonly used global LV strains. Our third validation study examined the reproducibility of these strain measures in both healthy and diseased populations. We established that OF-based strain measures demonstrate repeatability comparable to that achieved by the latest commercial software commonly used in clinical research to estimate 2D or 3D strain.
These studies were driven in large part by the absence of a ground truth or accepted gold standard of 3D strain measurements in the human LV. However, cardiac magnetic resonance imaging has had considerable success in measuring some forms of strain in the human LV. We therefore began to develop an image-processing pipeline to derive strain estimates from a new pulse sequence called 3D-DENSE. We further sought to improve the OF pipeline by automating the process of tracking the LV border. To this end, we developed a level-set based technique which tracks the LV endocardium. Our evaluation of its performance on RT3DE data confirmed that this method performs within the limits of inter-observer variability.
Overall, our pilot studies of OF-based strain estimation demonstrate that the technique possesses several promising features for improving cardiologists’ ability to quantify and interpret the complex three-dimensional deformations of the human LV
Validation of optical-flow for quantification of myocardial deformations on simulated RT3D ultrasound
Quantitative analysis of cardiac motion is of great clinical interest in assessing ventricular function. Real-time 3-D (RT3D) ultrasound transducers provide valuable fourdimensional information, from which quantitative measures of cardiac function can be extracted. Previously, we presented a method based on four-dimensional optical flow motion estimation for anatomical tracking of myocardium in RT3D ultrasound, from which myocardial displacement fields and dynamic cardiac metrics were computed. In this paper, in order to quantitatively validate our method, we build a truly 3D mathematical phantom of cardiac tissue and blood. Distinguished from previous studies, our work further decomposes tissue impedance into cell kernels and processes all functions in 3D. Instead of simply modeling the myocardium, a “quasi-LV” phantom is built including myocardium and blood. Also all ultrasound probe parameters used in this work are directly estimated from clinical RT3D data instead of using common parameters from 2D transducers. Based on this phantom, simulated RT3D ultrasound data sets are generated for validation to assess the performance of an optical flow based method in tracking myocardial tissues. 1
Eddy current pulsed thermography for non-destructive evaluation of carbon fibre reinforced plastic for wind turbine blades
PhD ThesisThe use of Renewable energy such as wind power has grown rapidly over the past ten
years. However, the poor reliability and high lifecycle costs of wind energy can limit
power generation. Wind turbine blades suffer from relatively high failure rates resulting
in long downtimes. The motivation of this research is to improve the reliability of wind
turbine blades via non-destructive evaluation (NDE) for the early warning of faults and
condition-based maintenance. Failure in wind turbine blades can be categorised as three
types of major defect in carbon fibre reinforced plastic (CFRP), which are cracks,
delaminations and impact damages. To detect and characterise those defects in their
early stages, this thesis proposes eddy current pulsed thermography (ECPT) NDE
method for CFRP-based wind turbine blades. The ECPT system is a redesigned
extension of previous work. Directional excitation is applied to overcome the problems
of non-homogeneous and anisotropic properties of composites in both numerical and
experimental studies. Through the investigation of the multiple-physical phenomena of
electromagnetic-thermal interaction, defects can be detected, classified and
characterised via numerical simulation and experimental studies.
An integrative multiple-physical ECPT system can provide transient thermal responses
under eddy current heating inside a sample. It is applied for the measurement and
characterisation of different samples. Samples with surface defects such as cracks are
detected from hot-spots in thermal images, whereas internal defects, like delamination
and impact damage, are detected through thermal or heat flow patterns.
For quantitative NDE, defect detection, characterisation and classification are carried
out at different levels to deal with various defect locations and fibre textures. Different
approaches for different applications are tested and compared via samples with crack,
delamination and impact damage. Comprehensive transient feature extraction at the
three different levels of the pixel, local area and pattern are developed and implemented
with respect to defect location in terms of the thickness and complexity of fibre texture.
Three types of defects are detected and classified at those three levels. The transient
responses at pixel level, flow patterns at local area level, and principal or independent
components at pattern level are derived for defect classification. Features at the pixel and local area levels are extracted in order to gain quantitative information about the
defects. Through comparison of the performance of evaluations at those three levels, the
pixel level is shown to be good at evaluating surface defects, in particular within uni-
directional fibres. Meanwhile the local area level has advantages for detecting deeper
defects such as delamination and impact damage, and in specimens with multiple fibre
orientations, the pattern level is useful for the separation of defective patterns and fibre
texture, as well as in distinguishing multiple defects.Engineering and Physical Sciences Research Council(EPSRC),
Frame Programme 7(FP7