Related Experiment Video
Updated: Aug 16, 2026
High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem
Published on: December 30, 2015
Quantitative proton magnetic resonance spectroscopic imaging: regional variations in the corpus callosum and cortical
Mahaveer N Degaonkar1, Martin G Pomper, Peter B Barker
1Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Baltimore, MD 21287, USA.
Purpose:
To evaluate regional variations of metabolite concentrations in normal adult brain cortical gray matter regions, and the genu and splenium of the corpus callosum, using proton magnetic resonance spectroscopic imaging (MRSI).
Materials And Methods:
Quantitative, multislice proton MRSI (TR/TE = 2000/280 msec) was performed in 12 normal human volunteers (age = 39 +/- 6 years, 7 male). Metabolite concentrations in selected cortical gray matter regions and the corpus callosum were estimated using the phantom replacement methodology.
Results:
Frontal and parietal gray matter (PGM) showed strong differences in choline-containing compound (Cho) concentrations; in particular, Cho was higher in mesial frontal gray matter than in both dorsolateral prefrontal cortex (P < 0.0005) and PGM (P < 0.004). In contrast, both N-acetylaspartate (NAA) and creatine (Cr) were relatively uniformly distributed in the cortical gray matter regions evaluated. Significant metabolic differences were found between the genu and splenium of the corpus callosum. Cho concentrations were significantly higher in genu than splenium (P < 0.005), while Cr was lower (P < 0.004). NAA showed a trend to be higher in the splenium than the genu (P = 0.05).
Conclusion:
Metabolite concentrations, particularly Cho, showed strong regional variations both within cortical gray matter regions and between the genu and splenium of the corpus callosum. Mesial frontal regions showed the highest Cho signals. Differences in spectra presumably reflect underlying changes in structure and cellular composition. Normal spectral variations should always be considered when evaluating pathology within those brain regions.
More Related Videos
13:56The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Published on: November 19, 2014
14:27Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
