Record Details

Title:
Electrical impedance based spectroscopy and tomography techniques for obesity and heart diseases [electronic resource] / Shell Xiaoxiao Zhang ; Yu-Chong Tai, advisor.
Author(s):
Imprint:
Pasadena, California : California Institute of Technology, 2017.
Description:
1 online resource (vi, 163 leaves) : digital (12 Mb), illustrations (some color).
Subject(s):
Series:
CIT theses ; 2017
Summary:
Despite advances in diagnosis and therapy, atherosclerosis cardiovascular disease remains the leading cause of morbidity and mortality. Predicting metabolically active atherosclerotic lesions has remained an unmet clinical need. Specially, atherosclerotic plaques that are prone to rupture are of extremely high-risk and can cause detrimental heart attacks and/or strokes, leading to sudden death. It has been shown that atheroscleroses is correlated to the level of obesity of an individual [1] Usually in clinical practice, the doctor will assess a patient's "risk factor" based on his or her Body Mass Index (BMS), and measurement of the waist circumference. Meanwhile the level of fatty droplet deposits in the liver is an important bio-marker to assess the patient's risk factor, however the patient will need to undergo radiation imaging such as CT scan or MRI scan. For the vulnerable plaques that can lead to sudden rupture, the ability to distinguish them at an early stage remains largely lacking. Therefore it is of great clinical interest to find improved diagnostic techniques to identify and localize such vulnerable plaques. Meanwhile, lipid has significantly lower electrical impedance than the rest of the vessel tissues in certain frequency bands [2]. In this thesis we explore spectroscopic and tomographic methods to characterize such plaques. In addition, with the Electrical Impedance Tomography method we will propose a novel method to detect fatty liver in an early stage with non-radiating and non-invasive manner.
Note:
Advisor and committee chair names found in the thesis' metadata record in the digital repository.
Dissertation note:
Thesis (Ph. D.) -- California Institute of Technology, 2017.
Bibliography, etc. note:
Includes bibliographical references.
Linked resources:
Caltech Connect
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 Record created 2017-11-08, last modified 2017-11-08


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