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Journal article

Constrained source space imaging: application to fast, region-based functional MRI.

Abstract:
A new technique called constrained source space imaging is introduced that holds promise for ultrafast acquisition of functional magnetic resonance imaging data. A sparse set of arbitrarily positioned, coarse voxels is first localized using radiofrequency selective excitation, from which magnetization signals are separated using only the spatial sensitivities of multichannel receiver coils, without the need for k-space encoding using imaging gradients. This method permits very fast acquisitions of targeted magnetization without complex or time-consuming image reconstruction techniques. Furthermore, because the data acquisition is performed without imaging gradients, T2* decays can be densely sampled and processed for contrast enhancement to improve functional magnetic resonance imaging data quality. Here, the constrained source space imaging technique is validated in proof-of-concept form, for a simple functional magnetic resonance imaging motor task using a prototype dual-band stimulated echo acquisition mode excitation to image four voxels at TR = 250 ms. Results demonstrate good voxel signal separation and good characterization of hemodynamic responses in primary motor cortices (M1) and supplementary motor areas through T2* fitting of the measured signals. With further refinement, the constrained source space imaging method has potential utility in a priori ROI-based functional magnetic resonance imaging experiments with TR values under 100 ms. Rapid, multivoxel measurements of other sources of MR signal contrast are also possible.

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Publisher copy:
10.1002/mrm.24557

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author


Journal:
Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine More from this journal
Volume:
70
Issue:
4
Pages:
1058-1069
Publication date:
2013-10-01
DOI:
EISSN:
1522-2594
ISSN:
0740-3194


Language:
English
Keywords:
Pubs id:
pubs:374489
UUID:
uuid:f69129dd-7ff3-4612-bf2b-22e04cf6f45d
Local pid:
pubs:374489
Source identifiers:
374489
Deposit date:
2013-11-16
ARK identifier:

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