Evidence map›Paper›PMID 35049104›Full record

ArticleMagnetic resonance in medicine2022

Evaluating diffusion dispersion across an extended range of b-values and frequencies: Exploiting gap-filled OGSE shapes, strong gradients, and spiral readouts.

Eric Seth Michael, Franciszek Hennel, Klaas Paul Pruessmann

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Article in Magnetic resonance in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

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0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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  7. Engineering clinical translation of OGSE diffusion MRI.Magnetic resonance in medicine · 2025
    Review
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Eric Seth MichaelInstitute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.ORCID 0000-0002-2513-4254
Franciszek HennelInstitute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.ORCID 0000-0003-0043-9921
Klaas Paul PruessmannInstitute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.ORCID 0000-0003-0009-8362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin-echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap-filled oscillating gradient shapes providing stronger diffusion encoding, and a high-performance gradient system is developed here and utilized to investigate the tradeoff between b-value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow-compensated variants are devised for experimental comparison.

methodsUsing DTI sequences, OGSE acquisitions were performed on three volunteers at b-values of 300, 500, and 1000 s/mm

resultsThe power law diffusion dispersion model was found to fit best to MD measurements acquired at b = 1000 s/mm

conclusionThe presented OGSE implementation provided an improved depiction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b-values rather than higher frequencies within the regimes employed in this study.

Indexed as

BrainDiffusion Magnetic Resonance ImagingDiffusionHumansMonte Carlo Methoddiffusion dispersiondiffusion MRIhigh-performance gradient systemOGSErestricted diffusionspiral readout

Identifiers

PMID35049104
PMCPMC9306807

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.