Persistent Link:
http://hdl.handle.net/10150/222845
Title:
New Models and Contrast Agents for Dynamic Contrast-Enhanced MRI
Author:
Cardenas Rodriguez, Julio César
Issue Date:
2012
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Angiogenesis is a fundamental driver of tumor biology and many other important aspect of human health. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) has been shown to be a valuable biomarker for the indirect assessment of angiogenesis. However, DCE-MRI is very specialized technique that has limitations. In this dissertation new models and contrast agents to address some of these limitations are presented. Chapter 1 presents an introduction to DCE-MRI, the rationale to asses tumor biology with this technique, the MRI pulses sequences and the standard pharmacokinetic modeling used for the analysis of DCE- MRI data. Chapter 2 describes the application of DCE-MRI to asses the response to the hypoxia-activated drug TH-302. It is shown that DCE-MRI can detect a response after only 24 hours of initiating therapy. In Chapter 3, a new model for the analysis of DCE-MRI is presented, the so-called Linear Reference Region Model (LRRM). This new model improves upon existing models and it was demonstrated that it is ~620 faster than current algorithms and 5 times less sensitive to noise, and more importantly less sensitive to temporal resolution which enables the analysis of DCE-MRI data obtained in the clinical setting, which opens a new area of study in clinical MRI. Chapter 4 describes the extension of the LRRM to estimate the absolute permeability of two fluorinated contrast agents; we call this approach the Reference Agent Model (RAM). In order to make this new model an experimental reality, a novel pulse sequence and contrast agents (CA) for ¹⁹F MRI were developed. Two contributions to the field of DCE-MRI are presented in this chapter, the first simultaneous ¹⁹F-DCE-MRI detection of two fluorinated CA in a mouse model of breast cancer, and the estimation of their relative permeability. RAM eliminates some of the physiological variables that affect DCE-MRI, which may improve its sensitivity and specificity. Finally, new potential applications of LRRM and RAM are discussed in Chapter 5.
Type:
text; Electronic Dissertation
Keywords:
Pharmacokinetics; Chemistry; Contrast Agent; DCE-MRI
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Chemistry
Degree Grantor:
University of Arizona
Advisor:
Pagel, Mark D.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleNew Models and Contrast Agents for Dynamic Contrast-Enhanced MRIen_US
dc.creatorCardenas Rodriguez, Julio Césaren_US
dc.contributor.authorCardenas Rodriguez, Julio Césaren_US
dc.date.issued2012-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractAngiogenesis is a fundamental driver of tumor biology and many other important aspect of human health. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) has been shown to be a valuable biomarker for the indirect assessment of angiogenesis. However, DCE-MRI is very specialized technique that has limitations. In this dissertation new models and contrast agents to address some of these limitations are presented. Chapter 1 presents an introduction to DCE-MRI, the rationale to asses tumor biology with this technique, the MRI pulses sequences and the standard pharmacokinetic modeling used for the analysis of DCE- MRI data. Chapter 2 describes the application of DCE-MRI to asses the response to the hypoxia-activated drug TH-302. It is shown that DCE-MRI can detect a response after only 24 hours of initiating therapy. In Chapter 3, a new model for the analysis of DCE-MRI is presented, the so-called Linear Reference Region Model (LRRM). This new model improves upon existing models and it was demonstrated that it is ~620 faster than current algorithms and 5 times less sensitive to noise, and more importantly less sensitive to temporal resolution which enables the analysis of DCE-MRI data obtained in the clinical setting, which opens a new area of study in clinical MRI. Chapter 4 describes the extension of the LRRM to estimate the absolute permeability of two fluorinated contrast agents; we call this approach the Reference Agent Model (RAM). In order to make this new model an experimental reality, a novel pulse sequence and contrast agents (CA) for ¹⁹F MRI were developed. Two contributions to the field of DCE-MRI are presented in this chapter, the first simultaneous ¹⁹F-DCE-MRI detection of two fluorinated CA in a mouse model of breast cancer, and the estimation of their relative permeability. RAM eliminates some of the physiological variables that affect DCE-MRI, which may improve its sensitivity and specificity. Finally, new potential applications of LRRM and RAM are discussed in Chapter 5.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectPharmacokineticsen_US
dc.subjectChemistryen_US
dc.subjectContrast Agenten_US
dc.subjectDCE-MRIen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineChemistryen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorPagel, Mark D.en_US
dc.contributor.committeememberMash, Eugeneen_US
dc.contributor.committeememberGhosh, Indraneelen_US
dc.contributor.committeememberTrouard, Theodoreen_US
dc.contributor.committeememberBacker, Amanda F.en_US
dc.contributor.committeememberPagel, Mark D.en_US
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