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The Capital Region of Denmark - a part of Copenhagen University Hospital
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Optimal voxel size for measuring global gray and white matter proton metabolite concentrations using chemical shift imaging.

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  1. Quantification of cerebral perfusion and cerebrovascular reserve using Turbo-QUASAR arterial spin labeling MRI

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  2. Coil profile estimation strategies for parallel imaging with hyperpolarized 13 C MRI

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  3. Gamma-aminobutyric acid edited echo-planar spectroscopic imaging (EPSI) with MEGA-sLASER at 7T

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  4. Comparison of prospective head motion correction with NMR field probes and an optical tracking system

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  5. Improved calculation of the equilibrium magnetization of arterial blood in arterial spin labeling

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  1. Brain Changes Induced by Electroconvulsive Therapy Are Broadly Distributed

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  2. Coil profile estimation strategies for parallel imaging with hyperpolarized 13 C MRI

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  3. Inductive measurement and encoding of k-space trajectories in MR raw data

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  4. Invited talk: MR safety: Regulatory aspects

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Quantification of gray and white matter levels of spectroscopically visible metabolites can provide important insights into brain development and pathological conditions. Chemical shift imaging offers a gain in efficiency for estimation of global gray and white matter metabolite concentrations compared to single voxel methods. In the present study, the optimal voxel size is calculated from segmented human brain data and accompanying field maps. The optimal voxel size is found to be approximately 8 cc, but a wide range of values, 4-64 cc, can be chosen with little increase in estimated concentration error (<15%). Magn Reson Med 44:10-18, 2000.
Original languageEnglish
JournalMagnetic Resonance in Medicine
Volume44
Issue number1
Pages (from-to)10-18
Number of pages8
ISSN0740-3194
Publication statusPublished - 2000

    Research areas

  • Body Water, Brain, Choline, Creatine, Humans, Image Processing, Computer-Assisted, Lactic Acid, Linear Models, Magnetic Resonance Spectroscopy, Mathematics, Protons, Signal Processing, Computer-Assisted

ID: 32493070