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Related Experiment Video

Updated: Mar 2, 2026

High-Sensitivity Nuclear Magnetic Resonance at Giga-Pascal Pressures: A New Tool for Probing Electronic and Chemical Properties of Condensed Matter under Extreme Conditions
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Normalizing data from GABA-edited MEGA-PRESS implementations at 3 Tesla.

Ashley D Harris1, Nicolaas A J Puts2, S Andrea Wijtenburg3

  • 1Department of Radiology, University of Calgary, Calgary, AB, Canada; Child and Adolescent Imaging Research (CAIR) Program, Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.

Magnetic Resonance Imaging
|May 9, 2017
PubMed
Summary
This summary is machine-generated.

This study quantifies GABA editing efficiency and macromolecule co-editing across MRI platforms. Applying these corrections reduces data variability, improving the standardization of GABA-edited MEGA-PRESS results.

Keywords:
Cross-platformEditing efficiencyGABAMEGA-PRESSMacromolecular co-editingMulti-site

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Neuroimaging
  • Quantitative Spectroscopy

Background:

  • Standardization is crucial for quantitative MRI methodologies.
  • Inconsistent GABA-edited MEGA-PRESS results stem from variations in editing efficiency and macromolecule co-editing.
  • Lack of measurement agreement limits multisite studies and literature comparisons.

Purpose of the Study:

  • To determine GABA editing efficiency (κ) and macromolecule co-editing (μ) constants for GE, Philips, and Siemens MEGA-PRESS implementations.
  • To apply these implementation-specific corrections to in vivo datasets.
  • To assess the impact of κ,μ-corrections on data variability and GABA levels.

Main Methods:

  • Phantom experiments were conducted to determine κ and μ values for three major MRI platforms.
  • Manufacturer-specific κ and μ values were calculated: κGE=0.436, κSiemens=0.366, κPhilips=0.394; μGE=0.83, μSiemens=0.625, μPhilips=0.75.
  • κ,μ-corrections were applied to multisubject and single-subject in vivo datasets, with results analyzed for creatine- and water-referenced data.

Main Results:

  • κ,μ-correction significantly decreased the coefficient of variation (CV) for creatine-referenced data in both in vivo datasets (multisubjects: 13% to 5%; single subject: 23% to 13%).
  • No significant effect on mean GABA levels was observed with κ,μ-correction for creatine-referenced data.
  • For water-referenced data, CV changes varied, and manufacturer remained a significant source of variance post-correction.

Conclusions:

  • Applying κ,μ-corrections improves the standardization of creatine-referenced GABA-edited MEGA-PRESS data across different MRI manufacturers.
  • While reducing inter-manufacturer variance for Cr-referenced data, other sources of variability persist.
  • Further standardization efforts are needed for robust multisite and comparative neuroimaging studies.