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Wiley, Magnetic Resonance in Medicine, 1(87), p. 220-235, 2021

DOI: 10.1002/mrm.28984

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An MR fingerprinting approach for quantitative inhomogeneous magnetization transfer imaging

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

PurposeMagnetization transfer (MT) and inhomogeneous MT (ihMT) contrasts are used in MRI to provide information about macromolecular tissue content. In particular, MT is sensitive to macromolecules, and ihMT appears to be specific to myelinated tissue. This study proposes a technique to characterize MT and ihMT properties from a single acquisition, producing both semiquantitative contrast ratios and quantitative parameter maps.Theory and MethodsBuilding on previous work that uses multiband RF pulses to efficiently generate ihMT contrast, we propose a cyclic steady‐state approach that cycles between multiband and single‐band pulses to boost the achieved contrast. Resultant time‐variable signals are reminiscent of an MR fingerprinting acquisition, except that the signal fluctuations are entirely mediated by MT effects. A dictionary‐based low‐rank inversion method is used to reconstruct the resulting images and to produce both semiquantitative MT ratio and ihMT ratio maps, as well as quantitative parameter estimates corresponding to an ihMT tissue model.ResultsPhantom and in vivo brain data acquired at 1.5 Tesla demonstrate the expected contrast trends, with ihMT ratio maps showing contrast more specific to white matter, as has been reported by others. Quantitative estimation of semisolid fraction and dipolar T1 was also possible and yielded measurements consistent with literature values in the brain.ConclusionBy cycling between multiband and single‐band pulses, an entirely MT‐mediated fingerprinting method was demonstrated. This proof‐of‐concept approach can be used to generate semiquantitative maps and quantitatively estimate some macromolecular‐specific tissue parameters.