Measurements of the spin-lattice relaxation rate in the rotating frame, R1rho, using spin-locking techniques have long been exploited to investigate relatively slow molecular motions and, more recently, to analyze chemical exchange. The variation of R1rho with spin-lock amplitude, or R1rho dispersion, provides the means to examine dynamic processes occurring on the time scale of the applied effective field, but corresponding techniques have been somewhat overlooked by the MRI community. Chemical exchange contributions to R1rho of protons in tissues are shown to dominate conventional dipole-dipole interactions at high fields, and R1rho dispersion depends on the exchange rate and chemical shift of the labile species. In addition, proton diffusion in the presence of intrinsic susceptibility gradients also contributes significantly to R1rho dispersion at low spin-lock amplitudes. Simulations and experiments performed in this work reveal these effects to largely be the dominant mechanisms influencing spin-locked relaxation at high static magnetic fields, and demonstrate the potential for using R1rho to characterize tissues across a variety of pathologies. Exchange-based R1rho methods are used to quantify exchange rates in solutions containing one or two solute pools and to produce images in which the contrast emphasizes the presence of metabolites exchanging at specific rates rather than with specific chemical shifts. A novel theory is derived that quantifies diffusion-based R1rho dispersion, which is subsequently applied to create parametric maps that reflect average sub-voxel microstructure and to calculate intrinsic gradient strengths in model systems of polystyrene microspheres and Red Blood Cells (RBCâs). This approach may further be used to estimate cell sizes and to emphasize vasculature of specific sizes in fMRI studies. Exchange and diffusion effects are also verified to be independent processes that may be analyzed simultaneously in biologically relevant applications. Collectively, R1rho dispersion methods provide a powerful alternative to traditional MRI methods and produce novel complementary information for quantitative tissue characterize.
|Date||18 March 2016|
|Creators||Spear, John Thomas|
|Contributors||John C. Gore, Daniel F. Gochberg, Michael S. Hutson, Erin C. Rericha, Thomas E. Yankeelov|
|Source Sets||Vanderbilt University Theses|
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