[CCoE Notice] PhD Defense Announcement

[Khator, Suresh]

PhD DEFENSE
By
Rafik Borji

November 29th 2010, Time: 10.30am-12.30pm, Room: N61 Engineering Building
Committee: Dr. M. Franchek, Dr. K. Grigoriadis, Dr. K. Larin, Dr. R. Metcalfe and Dr. Leang-San Shieh

MODELING ULTRASOUND WAVE PROPAGATION FOR TISSUE CHARACTERIZATION
There is an unfilled need for new health prognostic methods and technologies with a real opportunity to integrate cost effective imaging methods with accurate health prognostics.  By enhancing the capability of imaging methods to cover health prognostics, total cardiovascular diseases (CVD) health care costs would be dramatically reduced and the quality of human life would be significantly improved. One clinically accepted cost effective CVD diagnostics method is the intravascular ultrasound (IVUS). State-of-the-art in ultrasound imaging is based on the reflection of ultrasound waves (frequencies up to 50 MHz) sent from the ultrasound transducer. Despite the wide use of IVUS, as a primary tool for CVD diagnosis especially in determining the plaque prone to form in the arterial wall, an objective plaque composition classification is not reached yet. Since this composition is fundamental to determine the degree of severity of the CVD, computational models have been developed to simulate the propagation and behavior of the ultrasonic waves inside the arterial wall.

This research seeks to develop computational model based ultrasound imaging as a first step to enable CVD prognosis. Physics based transmission line matrix (TLM) computational model will be created where a fundamental understanding of ultrasound wave propagation in living tissue is captured. Moreover, the ultrasound wave propagation through healthy and plaque burden (hard and soft plaque) segments will be fundamentally understood and modeled.

The second primary step in this work is the development of advance adaptive image recovery modeling techniques (time domain system identification techniques) that characterize the tissue properties. Plaque burden and composition (such as hard and soft plaque) within the artery wall will be modeled using parametric techniques.   The outcome from these computations is the assignment of traditional lumped parameter mechanical (tissue) elements (first order system) to artery composition detected from the ultrasound wave. These parameters are paramount in the determination of the plaque acoustical and mechanical properties. These first order models have shown the ability of quantitatively characterizing different plaques based on their acoustic properties.

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