Literature DB >> 27037720

Incorporating dixon multi-echo fat water separation for novel quantitative magnetization transfer of the human optic nerve in vivo.

Alex K Smith1,2, Richard D Dortch1,2,3, Lindsey M Dethrage2, Bailey D Lyttle2, Hakmook Kang2,4,5, E Brian Welch1,2,3, Seth A Smith1,2,3,6.   

Abstract

PURPOSE: The optic nerve (ON) represents the sole pathway between the eyes and brain; consequently, diseases of the ON can have dramatic effects on vision. However, quantitative magnetization transfer (qMT) applications in the ON have been limited to ex vivo studies, in part because of the fatty connective tissue that surrounds the ON, confounding the magnetization transfer (MT) experiment. Therefore, the aim of this study was to implement a multi-echo Dixon fat-water separation approach to remove the fat component from MT images.
METHODS: MT measurements were taken in a single slice of the ON and frontal lobe using a three-echo Dixon readout, and the water and out-of-phase images were applied to a two-pool model in ON tissue and brain white matter to evaluate the effectiveness of using Dixon fat-water separation to remove fatty tissue from MT images.
RESULTS: White matter data showed no significant differences between image types; however, there was a significant increase (p < 0.05) in variation in the out-of-phase images in the ON relative to the water images.
CONCLUSIONS: The results of this study demonstrate that Dixon fat-water separation can be robustly used for accurate MT quantification of anatomies susceptible to partial volume effects resulting from fat. Magn Reson Med 77:707-716, 2017.
© 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  Dixon method; fat-water separation; optic nerve; qMT; quantitative magnetization transfer

Mesh:

Substances:

Year:  2016        PMID: 27037720      PMCID: PMC5045743          DOI: 10.1002/mrm.26164

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  63 in total

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Review 9.  FSL.

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