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A FLUID STRUCTURE INTERACTION MODEL OF INTRACORONARY ATHEROSCLEROTIC PLAQUE RUPTURE
Title
A FLUID STRUCTURE INTERACTION MODEL OF INTRACORONARY ATHEROSCLEROTIC PLAQUE RUPTURE.
Creator
TEUMA-MELAGO, Eric, Ilegbusi, Olusegun, University of Central Florida
Abstract / Description
Plaque rupture with superimposed thrombosis is the primary cause of acute coronary syndromes of unstable angina, myocardial infarction and sudden death. Although intensive studies in the past decade have shed light on the mechanism that causes unstable atheroma, none has directly addressed the clinical observation that most myocardial infarction (MI) patients have moderate stenoses (less than 50%). Considering the important role the arterial wall compliance and pulsitile blood flow play in...
Show morePlaque rupture with superimposed thrombosis is the primary cause of acute coronary syndromes of unstable angina, myocardial infarction and sudden death. Although intensive studies in the past decade have shed light on the mechanism that causes unstable atheroma, none has directly addressed the clinical observation that most myocardial infarction (MI) patients have moderate stenoses (less than 50%). Considering the important role the arterial wall compliance and pulsitile blood flow play in atheroma rupture, fluid-structure interaction (FSI) phenomenon has been of interest in recent studies. In this thesis, the impact is investigated numerically of coupled blood flow and structural dynamics on coronary plaque rupture. The objective is to determine a unique index that can be used to characterize plaque rupture potential. The FSI index, developed in this study for the first time derives from the theory of buckling of thin-walled cylinder subjected to radial pressure. Several FSI indices are first defined by normalizing the predicted hemodynamic endothelial shear stress by the structural stresses, specifically, by the maximum principal stress (giving the ratio ), and the Von Mises stress (giving the ratio ). The predicted at the location of maximum (i.e { }) denoted , is then chosen to characterize plaque rupture through systematic investigation of a variety of plaque characteristics and simulated patient conditions. The conditions investigated include varying stenosis levels ranging from 20% to 70%, blood pressure drop ranging from 3125 Pa/m to 9375 Pa/m, fibrous cap thickness ranging from to , lipid pool location ranging from the leading to the trailing edge of plaque, lipid pool volume relative to stenosis volume ranging from 24% to 80%, Calcium volume relative to stenosis volume ranging from 24% to 80% and arterial remodeling. The predicted varies with the stenosis severity and indicates that the plaques investigated are prone to rupture at approximately 40-45% stenosis levels. It predicts that high pressure significantly lowers the threshold stenosis rate for plaque rupture. In addition, the plaque potential to rupture increases for relatively thin fibrous cap, lipid core located near the leading plaque shoulder, and dramatically for relative lipid pool volume above 60%. However, calcium deposit has marginal effect on plaque rupture. Overall, the predicted results are consistent with clinical observations, indicating that the has the potential to characterize plaque rupture when properly established. In the appendix, the unsteady flow in a collapsible tube model of a diseased artery is solved analytically. The novelty of our approach is that the set of governing equations is reduced to a single integro-differential equation in the transient state. The equation was solved using the finite difference method to obtain the pressure and compliant wall behavior. The analytical approach is less computer-intensive than solving the full set of governing equations. The predicted membrane deflection is quite large at low inlet velocity, suggesting possible approach to breakdown in equilibrium. As the transmural pressure increases with wall deflection, bulges appear at the ends of the membrane indicating critical stage of stability, consistent with previous studies. An increase in wall thickness reduces the wall deflection and ultimately results in its collapse. The collapse is due to breakdown in the balance of wall governing equation. An increase in internal pressure is required to maintain membrane stability.
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Date Issued
2006
Identifier
CFE0001471, ucf:47084
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001471
EFFICIENT TECHNIQUES FOR RELEVANCE FEEDBACK PROCESSING IN CONTENT-BASED IMAGE RETRIEVAL
Title
EFFICIENT TECHNIQUES FOR RELEVANCE FEEDBACK PROCESSING IN CONTENT-BASED IMAGE RETRIEVAL.
Creator
Liu, Danzhou, Hua, Kien, University of Central Florida
Abstract / Description
In content-based image retrieval (CBIR) systems, there are two general types of search: target search and category search. Unlike queries in traditional database systems, users in most cases cannot specify an ideal query to retrieve the desired results for either target search or category search in multimedia database systems, and have to rely on iterative feedback to refine their query. Efficient evaluation of such iterative queries can be a challenge, especially when the multimedia database...
Show moreIn content-based image retrieval (CBIR) systems, there are two general types of search: target search and category search. Unlike queries in traditional database systems, users in most cases cannot specify an ideal query to retrieve the desired results for either target search or category search in multimedia database systems, and have to rely on iterative feedback to refine their query. Efficient evaluation of such iterative queries can be a challenge, especially when the multimedia database contains a large number of entries, and the search needs many iterations, and when the underlying distance measure is computationally expensive. The overall processing costs, including CPU and disk I/O, are further emphasized if there are numerous concurrent accesses. To address these limitations involved in relevance feedback processing, we propose a generic framework, including a query model, index structures, and query optimization techniques. Specifically, this thesis has five main contributions as follows. The first contribution is an efficient target search technique. We propose four target search methods: naive random scan (NRS), local neighboring movement (LNM), neighboring divide-and-conquer (NDC), and global divide-and-conquer (GDC) methods. All these methods are built around a common strategy: they do not retrieve checked images (i.e., shrink the search space). Furthermore, NDC and GDC exploit Voronoi diagrams to aggressively prune the search space and move towards target images. We theoretically and experimentally prove that the convergence speeds of GDC and NDC are much faster than those of NRS and recent methods. The second contribution is a method to reduce the number of expensive distance computation when answering k-NN queries with non-metric distance measures. We propose an efficient distance mapping function that transfers non-metric measures into metric, and still preserves the original distance orderings. Then existing metric index structures (e.g., M-tree) can be used to reduce the computational cost by exploiting the triangular inequality property. The third contribution is an incremental query processing technique for Support Vector Machines (SVMs). SVMs have been widely used in multimedia retrieval to learn a concept in order to find the best matches. SVMs, however, suffer from the scalability problem associated with larger database sizes. To address this limitation, we propose an efficient query evaluation technique by employing incremental update. The proposed technique also takes advantage of a tuned index structure to efficiently prune irrelevant data. As a result, only a small portion of the data set needs to be accessed for query processing. This index structure also provides an inexpensive means to process the set of candidates to evaluate the final query result. This technique can work with different kernel functions and kernel parameters. The fourth contribution is a method to avoid local optimum traps. Existing CBIR systems, designed around query refinement based on relevance feedback, suffer from local optimum traps that may severely impair the overall retrieval performance. We therefore propose a simulated annealing-based approach to address this important issue. When a stuck-at-a-local-optimum occurs, we employ a neighborhood search technique (i.e., simulated annealing) to continue the search for additional matching images, thus escaping from the local optimum. We also propose an index structure to speed up such neighborhood search. Finally, the fifth contribution is a generic framework to support concurrent accesses. We develop new storage and query processing techniques to exploit sequential access and leverage inter-query concurrency to share computation. Our experimental results, based on the Corel dataset, indicate that the proposed optimization can significantly reduce average response time while achieving better precision and recall, and is scalable to support a large user community. This latter performance characteristic is largely neglected in existing systems making them less suitable for large-scale deployment. With the growing interest in Internet-scale image search applications, our framework offers an effective solution to the scalability problem.
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Date Issued
2009
Identifier
CFE0002728, ucf:48162
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0002728