Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla

Ashley D. Harris, Nicolaas A.J. Puts, S. Andrea Wijtenburg, Laura M. Rowland, Mark Mikkelsen, Peter B. Barker, C. John Evans, Richard A.E. Edden

Research output: Contribution to journalArticle

Abstract

Standardization of results is an important milestone in the maturation of any truly quantitative methodology. For instance, a lack of measurement agreement across imaging platforms limits multisite studies, between-study comparisons based on the literature, and inferences based on and the generalizability of results. In GABA-edited MEGA-PRESS, two key sources of differences between implementations are: differences in editing efficiency of GABA and the degree of co-editing of macromolecules (MM). In this work, GABA editing efficiency κ and MM-co-editing μ constants are determined for three widely used MEGA-PRESS implementations (on the most common MRI platforms; GE, Philips, and Siemens) by phantom experiments. Implementation-specific κ,μ-corrections were then applied to two in vivo datasets, one consisted of 8 subject scanned on the three platforms and the other one subject scanned eight times on each platform. Manufacturer-specific κ and μ values were determined as: κGE = 0.436, κSiemens = 0.366 and κPhilips = 0.394 and μGE = 0.83, μSiemens = 0.625 and μPhilips = 0.75. Applying the κ,μ-correction on the Cr-referenced data decreased the coefficient of variation (CV) of the data for both in vivo data sets (multisubjects: uncorrected CV = 13%, κ,μ-corrected CV = 5%, single subject: uncorrected CV = 23%, κ,μ-corrected CV = 13%) but had no significant effect on mean GABA levels. For the water-referenced results, CV increased in the multisubject data (uncorrected CV = 6.7%, κ,μ-corrected CV = 14%) while it decreased in the single subject data (uncorrected CV = 24%, κ,μ-corrected CV = 21%) and manufacturer was a significant source of variance in the κ,μ-corrected data. Applying a correction for editing efficiency and macromolecule contamination decreases the variance between different manufacturers for creatine-referenced data, but other sources of variance remain.

LanguageEnglish (US)
Pages8-15
Number of pages8
JournalMagnetic Resonance Imaging
Volume42
DOIs
StatePublished - Oct 1 2017

Fingerprint

Macromolecules
gamma-Aminobutyric Acid
Magnetic resonance imaging
Standardization
Creatine
Information Storage and Retrieval
Contamination
Imaging techniques
Water
Experiments
Datasets

Keywords

  • Cross-platform
  • Editing efficiency
  • GABA
  • Macromolecular co-editing
  • MEGA-PRESS
  • Multi-site

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla. / Harris, Ashley D.; Puts, Nicolaas A.J.; Wijtenburg, S. Andrea; Rowland, Laura M.; Mikkelsen, Mark; Barker, Peter B.; Evans, C. John; Edden, Richard A.E.

In: Magnetic Resonance Imaging, Vol. 42, 01.10.2017, p. 8-15.

Research output: Contribution to journalArticle

Harris AD, Puts NAJ, Wijtenburg SA, Rowland LM, Mikkelsen M, Barker PB et al. Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla. Magnetic Resonance Imaging. 2017 Oct 1;42:8-15. Available from, DOI: 10.1016/j.mri.2017.04.013
Harris, Ashley D. ; Puts, Nicolaas A.J. ; Wijtenburg, S. Andrea ; Rowland, Laura M. ; Mikkelsen, Mark ; Barker, Peter B. ; Evans, C. John ; Edden, Richard A.E./ Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla. In: Magnetic Resonance Imaging. 2017 ; Vol. 42. pp. 8-15
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