Robust diffusion tensor imaging by spatiotemporal encoding: Principles and in vivo demonstrations

Eddy Solomon, Gilad Liberman, Noam Nissan, Lucio Frydman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Purpose: Evaluate the usefulness of single-shot and of interleaved spatiotemporally encoded (SPEN) methods to perform diffusion tensor imaging (DTI) under various preclinical and clinical settings. Methods: A formalism for analyzing SPEN DTI data is presented, tailored to account for the spatially dependent b-matrix weightings introduced by the sequence's use of swept pulses acting while in the presence of field gradients. Using these b-matrix calculations, SPEN's ability to deliver DTI measurements was tested on phantoms as well as ex vivo and in vivo. In the latter case, DTI involved scans on mice brains and on human lactating breasts. Results: For both ex vivo and in vivo investigations, SPEN data proved less sensitive to distortions arising from Bo field inhomogeneities and from eddy currents, than conventional single-shot alternatives. Further resolution enhancement could be achieved using referenceless methods for interleaved SPEN data acquisitions. Conclusion: The robustness of SPEN-based sequences vis-à-vis field instabilities and heterogeneities, enables the implementation of DTI experiments with good sensitivity and resolution even in challenging environments in both preclinical and clinical settings. Magn Reson Med 77:1124–1133, 2017.

Original languageEnglish
Pages (from-to)1124-1133
Number of pages10
JournalMagnetic Resonance in Medicine
Volume77
Issue number3
DOIs
StatePublished - 1 Mar 2017
Externally publishedYes

Funding

FundersFunder number
Kimmel Institute for Magnetic Resonance
Weizmann MRI team
Horizon 2020 Framework Programme633888
Perlman Family Foundation
European Commission
Israel Science Foundation

    Keywords

    • b-value calculations
    • brain DTI
    • breast DTI
    • diffusion-tensor imaging – DTI
    • spatiotemporal encoding – SPEN

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