Volume 74, Issue 5 pp. 1317-1326
Full Paper

Removal of cerebrospinal fluid partial volume effects in quantitative magnetization transfer imaging using a three-pool model with nonexchanging water component

Pouria Mossahebi

Pouria Mossahebi

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

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Andrew L. Alexander

Andrew L. Alexander

Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

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Aaron S. Field

Aaron S. Field

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Department of Biomedical Engineering, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

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Alexey A. Samsonov

Corresponding Author

Alexey A. Samsonov

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA

Correspondence to: Alexey A. Samsonov, Ph.D., Department of Radiology, University of Wisconsin School of Medicine and Public Health, 1111 Highland Avenue, Room 1117, Madison, WI 53705. E-mail: [email protected]Search for more papers by this author
First published: 13 November 2014
Citations: 16

Part of this study was presented at the 23rd Annual Meeting of the ISMRM, Milan, Italy, 2014 (Abstract #207).

Abstract

Purpose

Parameters of the two-pool model describing magnetization transfer (MT) in macromolecule-rich tissues may be significantly biased in partial volume (PV) voxels containing cerebrospinal fluid (CSF). The purpose of this study was to develop a quantitative MT (qMT) method that provides indices insensitive to CSF PV averaging.

Theory and Methods

We propose a three-pool MT model, in which PV macro-compartment is modeled as an additional nonexchanging water pool. We demonstrate the feasibility of model parameter estimation from several MT-weighted spoiled gradient echo datasets. We validated the three-pool model in numerical, phantom, and in vivo studies.

Results

PV averaging with the free water compartment reduces all qMT parameters, most significantly affecting macromolecular proton fraction (MPF) and cross-relaxation rate. Monte-Carlo simulations confirmed stability of the three-pool model fit. Unlike the standard two-pool model, the three-pool model qMT parameters were not affected by PV averaging in simulations and phantom studies. The three-pool model fit allowed CSF PV correction in brain PV voxels and resulted in good correlation with standard two-pool model parameters in non-PV voxels.

Conclusion

Quantitative MT imaging based on a three-pool model with a non-exchanging water component yields a set of CSF-insensitive qMT parameters, which may improve MPF-based assessment of myelination in structures strongly affected by CSF PV averaging such as brain gray matter. Magn Reson Med 74:1317–1326, 2015. © 2014 Wiley Periodicals, Inc.

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