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Frequency-selective Methods for Hyperpolarized 13C Cardiac Magnetic Resonance Imaging

Heart failure is a complex clinical syndrome in which the heart cannot pump sufficient blood and nutrients to the organs in the body. Increasingly, alterations in cardiac energetics are being implicated as playing an important role in the pathogenesis of heart failure. An understanding of specific metabolic switches which occur during the development of heart failure in patients would be greatly beneficial as a new diagnostic method and for the development of new therapies for patients with failing hearts.

This thesis deals with the non-invasive assessment of metabolism in the heart. New magnetic resonance imaging (MRI) methods for metabolic characterization of the heart using hyperpolarized carbon-13 MRI are presented. Spatially resolved images of hyperpolarized 13C substrates and their downstream products can provide insight into real-time metabolic processes occurring in vivo, within minutes of injection of a pre-polarized 13C-labeled substrate. Conventional 3D spectroscopic acquisitions require in excess of 100 excitations, making it challenging to acquire full cardiac and respiratory-gated, whole-heart metabolic volumes.

Each of the developments described in this thesis is intended to advance cardiac hyperpolarized 13C metabolic imaging towards a routine, clinical exam which can be used for prognosis and treatment optimization in patients with cardiovascular disease. The major technical development is a new interleaved-frequency, time-resolved MRI pulse sequence that can provide robust and reliable measurements of cardiac metabolic signals. The technique was applied to several realistic pre-clinical models of cardiac disease and the work presented will hopefully lead towards significant improvement in the management of patients with heart failure.

Identiferoai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/34779
Date17 December 2012
CreatorsLau, Angus
ContributorsCunningham, Charles H.
Source SetsUniversity of Toronto
Languageen_ca
Detected LanguageEnglish
TypeThesis

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