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  Fast interleaved multislice T1 mapping: Model-based reconstruction of single-shot inversion-recovery radial FLASH.

Wang, X., Voit, D., Roeloffs, V. B., Uecker, M., & Frahm, J. (2018). Fast interleaved multislice T1 mapping: Model-based reconstruction of single-shot inversion-recovery radial FLASH. Computational and Mathematical Methods in Medicine, 2018: 2560964. doi:10.1155/2018/2560964.

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Wang, X.1, Author           
Voit, D.1, Author           
Roeloffs, V. B.1, Author           
Uecker, M., Author
Frahm, J.1, Author           
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1Biomedical NMR Research GmbH, MPI for Biophysical Chemistry, Max Planck Society, ou_578634              

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 Abstract: Purpose. To develop a high-speed multislice T1 mapping method based on a single-shot inversion-recovery (IR) radial FLASH acquisition and a regularized model-based reconstruction. Methods. Multislice radial k-space data are continuously acquired after a single nonselective inversion pulse using a golden-angle sampling scheme in a spoke-interleaved manner with optimized flip angles. Parameter maps and coil sensitivities of each slice are estimated directly from highly undersampled radial k-space data using a model-based nonlinear inverse reconstruction in conjunction with joint sparsity constraints. The performance of the method has been validated using a numerical and experimental T1 phantom as well as demonstrated for studies of the human brain and liver at 3T. Results. The proposed method allows for 7 simultaneous T1 maps of the brain at 0.5 x 0.5 x 4 mm(3) resolution within a single IR experiment of 4 s duration. Phantom studies confirm similar accuracy and precision as obtained for a single-slice acquisition. For abdominal applications, the proposed method yields three simultaneous T1 maps at 1.25 x 1.25 x 6 mm(3) resolution within a 4 s breath hold. Conclusion. Rapid, robust, accurate, and precise multislice T1 mapping may be achieved by combining the advantages of a model-based nonlinear inverse reconstruction, radial sampling, parallel imaging, and compressed sensing.

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Language(s): eng - English
 Dates: 2018-08-13
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1155/2018/2560964
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Title: Computational and Mathematical Methods in Medicine
Source Genre: Journal
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Pages: 8 Volume / Issue: 2018 Sequence Number: 2560964 Start / End Page: - Identifier: -