title: Extension of the double-wave-vector diffusion-weighting experiment to multiple concatenations.
abstract: Experiments involving two diffusion-weightings in a single acquisition, so-called double- or two-wave-vector experiments, have recently been applied to measure the microscopic anisotropy in macroscopically isotropic samples or to estimate pore or compartment sizes. These informations are derived from the signal modulation observed when varying the wave vectors' orientations. However, the modulation amplitude can be small and, for short mixing times between the two diffusion-weightings, decays with increased gradient pulse lengths which hampers its detectability on whole-body MR systems. Here, an approach is investigated that involves multiple concatenations of the two diffusion-weightings in a single experiment. The theoretical framework for double-wave-vector experiments of fully restricted diffusion is adapted and the corresponding tensor approach recently presented for short mixing times extended and compared to numerical simulations. It is shown that for short mixing times (i) the extended tensor approach well describes the signal behavior observed for multiple concatenations and (ii) the relative amplitude of the signal modulation increases with the number of concatenations. Thus, the presented extension of the double-wave-vector experiment may help to improve the detectability of the signal modulations observed for short mixing times, in particular on whole-body MR systems with their limited gradient amplitudes.
authors.affiliation: Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. j.finsterbusch@uke.uni-hamburg.de
authors.forename: Jürgen
authors.initials: J
authors.lastname: Finsterbusch
mesh_terms: D000465:Algorithms; D048429:Cell Size; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D016062:Porosity; D012815:Signal Processing, Computer-Assisted