Assessment of exercise-stimulated tissue oxygenation in calf muscle with functional MRI

Update Item Information
Publication Type honors thesis
School or College College of Science
Department Physics and Astronomy
Faculty Mentor Eun Kee (E.K.) Jeong
Creator Renz, Andy
Title Assessment of exercise-stimulated tissue oxygenation in calf muscle with functional MRI
Year graduated 2016
Date 2016-04
Description Peripheral artery disease (PAD) affects millions of patients in the USA, and effective diagnosis and management of PAD is a major clinical goal. One promising avenue of research towards the goal is through functional MRI, which provides non-invasive measurement of tissue oxygenation. For a group of healthy and PAD subjects, we performed functional MRI (magnetic resonance imaging) scans immediately after plantar flexion, with variable loads, to monitor muscle oxygenation (pO2) during the exercise recovery. In the project, I built a mathematical model that characterizes the kinetics of blood oxygen in calf muscle during exercise recovery, based on MR physics, and implemented the model using Matlab. In conjunction, parameters were chosen that described the data (i.e. initial value or minimum), called data parameter analysis, which were compared amongst the subjects. The Matlab grograms included the oxygen kinetic model and a curve-fitting algorithm driven by least-square optimization technique as well as the data parameter analysis. With the programs. we processed the functional MRI data. and compared the model and data parameter values between the healthy and PAD subjects, and between individuals with different exercise loads. The comparison results showed that the functional parameters from the proposed model and data features were able to differentiate healthy versus PAD, and were sensitive to exercise intensity. This study suggests that exercise-recovery MRI is a promising tool for functional assessment of calf muscle and has potential in improving clinical management of PAD.
Type Text
Publisher University of Utah
Subject Arteries - Diseases - Diagnosis; Magnetic resonance imaging - Research; Calf muscle; Peripheral arterial disease; MATLAB
Language eng
Rights Management (c) Andy Renz
Format Medium application/pdf
Format Extent 25,087 bytes
Identifier honors/id/85
Permissions Reference URL https://collections.lib.utah.edu/details?id=1292305
ARK ark:/87278/s6m93jwm
Setname ir_htoa
ID 205737
Reference URL https://collections.lib.utah.edu/ark:/87278/s6m93jwm
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