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| Home > Publications database > Iterative reconstruction of radially-sampled (31)P bSSFP data using prior information from (1)H MRI. |
| Journal Article | DKFZ-2017-00419 |
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2017
Elsevier Science
Amsterdam [u.a.]
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Please use a persistent id in citations: doi:10.1016/j.mri.2016.11.013
Abstract: The purpose of this study is to improve direct phosphorus ((31)P) MR imaging. Therefore, 3D density-adapted radially-sampled balanced steady-state free precession (bSSFP) sequences were developed and an iterative approach exploiting additional anatomical information from hydrogen ((1)H) data was evaluated. Three healthy volunteers were examined at B0=7T in order to obtain the spatial distribution of the phosphocreatine (PCr) intensities in the human calf muscle with a nominal isotropic resolution of 10mm in an acquisition time of 10min. Three different bSSFP gradient schemes were investigated. The highest signal-to-noise ratio (SNR) was obtained for a scheme with two point-reflected density-adapted gradients. Furthermore, the conventional reconstruction based on a gridding algorithm was compared to an iterative method using an (1)H MRI constraint in terms of a segmented binary mask, which comprises prior knowledge. The parameters of the iterative approach were optimized and evaluated by simulations featuring (31)P MRI parameters. Thereby, partial volume effects as well as Gibbs ringing artifacts could be reduced. In conclusion, the iterative reconstruction of (31)P bSSFP data using an (1)H MRI constraint is appropriate for investigating regions where sharp tissue boundaries occur and leads to images that represent the real PCr distributions better than conventionally reconstructed images.
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