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Multi-shot Echo Planar Imaging for accelerated Cartesian MR Fingerprinting: An alternative to conventional spiral MR Fingerprinting.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Benjamin, Arnold Julian Vinoj 
Gómez, Pedro A 
Golbabaee, Mohammad 
Mahbub, Zaid Bin 
Sprenger, Tim 

Abstract

PURPOSE: To develop an accelerated Cartesian MRF implementation using a multi-shot EPI sequence for rapid simultaneous quantification of T1 and T2 parameters. METHODS: The proposed Cartesian MRF method involved the acquisition of highly subsampled MR images using a 16-shot EPI readout. A linearly varying flip angle train was used for rapid, simultaneous T1 and T2 quantification. The results were compared to a conventional spiral MRF implementation. The acquisition time per slice was 8s and this method was validated on two different phantoms and three healthy volunteer brains in vivo. RESULTS: Joint T1 and T2 estimations using the 16-shot EPI readout are in good agreement with the spiral implementation using the same acquisition parameters (<4% deviation for T1 and <6% deviation for T2). The T1 and T2 values also agree with the conventional values previously reported in the literature. The visual qualities of fine brain structures in the multi-parametric maps generated by multi-shot EPI-MRF and Spiral-MRF implementations were comparable. CONCLUSION: The multi-shot EPI-MRF method generated accurate quantitative multi-parametric maps similar to conventional Spiral-MRF. This multi-shot approach achieved considerable k-space subsampling and comparatively short TRs in a similar manner to spirals and therefore provides an alternative for performing MRF using an accelerated Cartesian readout; thereby increasing the potential usability of MRF.

Description

Keywords

Cartesian MRF, Multi-shot EPI, Quantitative maps, Algorithms, Brain, Echo-Planar Imaging, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, Phantoms, Imaging, Reference Values

Journal Title

Magn Reson Imaging

Conference Name

Journal ISSN

0730-725X
1873-5894

Volume Title

61

Publisher

Elsevier BV
Sponsorship
The research leading to these results has received funding from the European Commission H2020 Framework Programme (H2020- MSCAITN- 2014), number 642685 MacSeNet, the Engineering and Physical Sciences Research Council (EPSRC) platform Compressed Quantitative MRI grant, number EP/M019802/1 and the Scottish Research Partnership in Engineering (SRPe) award, number SRPe PECRE1718/ 17.