Frequency difference mapping applied to the corpus callosum at 7T

Purpose Frequency difference mapping (FDM) is a phase processing technique which characterizes the nonlinear temporal evolution of the phase of gradient echo (GE) signals. Here, a novel FDM‐processing algorithm is introduced, which is shown to reveal information about white matter microstructure. Un...

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Bibliographic Details
Published inMagnetic resonance in medicine Vol. 81; no. 5; pp. 3017 - 3031
Main Authors Tendler, Benjamin C., Bowtell, Richard
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.05.2019
John Wiley and Sons Inc
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Summary:Purpose Frequency difference mapping (FDM) is a phase processing technique which characterizes the nonlinear temporal evolution of the phase of gradient echo (GE) signals. Here, a novel FDM‐processing algorithm is introduced, which is shown to reveal information about white matter microstructure. Unlike some other phase‐processing techniques, the FDM algorithm presented here does not require the use of phase unwrapping or sophisticated image processing. It uses a series of scaled complex divisions to unwrap phase and remove background fields. Methods Ten healthy subjects underwent a series of single‐slice, sagittal multi‐echo GE scans at 7T with the slice positioned at the midline. Phase data were processed with the novel FDM algorithm, and the temporal evolution of the magnitude signal and frequency difference was examined in 5 regions of the corpus callosum (CC; genu, anterior body, middle body, posterior body, and splenium). Results Consistent frequency difference contrast relative to surrounding tissue was observed in all subjects in the CC and in other white matter regions where the nerve fibers run perpendicular to B0, such as the superior cerebellar peduncle. Examination of the frequency difference curves shows distinct variations over the CC, with the genu and splenium displaying larger frequency differences than the other regions (in addition to a faster decay of signal magnitude). Conclusion The novel FDM algorithm presented here yields images sensitive to tissue microstructure and microstructural differences over the CC in a simple manner, without the requirement for phase unwrapping or sophisticated image processing.
Bibliography:Funding information
Medical Research Council, Grant Number: G0901321; an EPSRC PhD studentship (1367067) awarded to B.C.T.
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ISSN:0740-3194
1522-2594
DOI:10.1002/mrm.27626