Gradient echoes: simplified.

Advances in real-time phase-contrast flow MRI using asymmetric radial gradient echoes.

PURPOSE To provide multidimensional velocity compensation for real-time phase-contrast flow MRI. METHODS The proposed method introduces asymmetric gradient echoes for highly undersampled radial FLASH MRI with phase-sensitive image reconstruction by regularized nonlinear inversion (NLINV). Using an adapted gradient delay correction the resulting image quality was analyzed by simulations and ex...

Multiplex RARE Dixon: a novel multislice RARE sequence applied to simultaneous slice fat-water Dixon imaging

Introduction Multislice excitation methods have been widely used to increase efficiency in volume coverage. In the simultaneous spin-echo refocusing sequence (SER) [1], two or more slices are excited simultaneously and refocused with a train of 180° pulses which act simultaneously on both slices. However, the SER sequence does not fulfil CPMG conditions, and requires special spoiler gradients t...

Magnetic Resonance in Medicine

Up to now, various methods have been proposed for spatial mapping of a spin distribution using NMR. Several of these methods use field gradient time modulation for high-speed data acquisition. One such method is the well-known echo-planar imaging ( I , 2). With this method, spin distributions can be imaged with a single spinecho train induced by one 90" pulse application. However, the method im...

Single-shot T(2)* mapping with 3D compensation of local susceptibility gradients in multiple regions.

Macroscopic magnetic field inhomogeneities severely limit sensitivity of blood oxygenation level-dependent (BOLD) functional MRI (fMRI) in frontal and central brain regions close to brain stem. A single-shot multiecho echo-planar imaging method (TurboPEPSI) was developed that combines quantitative T(2)* mapping with gradient compensation of local susceptibility inhomogeneities in multiple volum...

Spin Diffusion Measurements: Spin Echoes in the Presence of a Time Dependent Field Gradient