KEYWORDS: Magnetic resonance imaging, Data acquisition, Arteries, Temporal resolution, Angiography, Signal to noise ratio, Gadolinium, Veins, Image quality, Magnetism
A method to improve time resolution in 3D contrast-enhanced magnetic resonance angiography (CE-MRA) is
proposed. A temporal basis based on prior knowledge of the contrast flow dynamics is applied to a sequence of
image reconstructions.
In CE-MRA a contrast agent (gadolinium) is injected into a peripheral vein and MR data is acquired as
the agent arrives in the arteries and then the veins of the region of clinical interest. The acquisition extends
over several minutes. Information is effectively measured in 3D k-space (spatial frequency space) one line at-atime.
That line may be along a Cartesian grid line in k-space, a radial line or a spiral trajectory. A complete
acquisition comprises many such lines but in order to improve temporal resolution, reconstructions are made from
only partial sets of k-space data. By imposing a basis for the temporal changes, based on prior expectation of the
smoothness of the changes in contrast concentration with time, it is demonstrated that a significant reduction
in artifacts caused by the under-sampling of k-space can be achieved. The basis is formed from a set of gamma
variate functions. Results are presented for a simulated set of 2D spiral-sampled CE-MRA data.
A hybrid method is presented which allows the acceleration of parallel MR imaging through combining the ideas
of compressed sensing with inversion of the imaging matrix. A novel data reordering is employed to enhance the
sparsity inherent in the image transform. Simulation results with actual head scan data are presented.
KEYWORDS: Data acquisition, Temporal resolution, Computer programming, Signal to noise ratio, Resonance enhancement, Magnetic resonance angiography, Magnetic resonance imaging, Angiography, Receivers, Image restoration
A new way of performing contrast enhanced magnetic resonance angiography (CE-MRA) is presented, in which the entire k-space is decomposed into interlaced subsets that are acquired sequentially. Based on a new parallel imaging technique, Generalized Unaliasing Incorporating object Support constraint and sensitivity Encoding (GUISE), reconstructions can be made using different subsets of k-space to reveal the level of contrast agent in the corresponding data acquisition time period. A proof-of-concept study using a custom made phantom was carried out to examine the utility of the new method. A quantity of contrast agent (copper sulfate solution) was injected into water flowing within a tube while data was acquired using an 8-coil receiver and the modified MRI sequence. A sequence of images was successfully reconstructed at high temporal resolution. This eliminated the need to precisely synchronize data acquisition with contrast arrival. Furthermore, subtraction of a pre-contrast data set prior to reconstruction, which eliminates the need for recovering the static background signal, has proven to be an effective way to improve the SNR and allow a higher temporal resolution to be achieved in recovering the dynamic signal containing contrast level change. Acceptably good reconstruction results were obtained at a temporal resolution equivalent to a 16-fold speed up compared to the time taken to fully sample k-space.
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