NeuroImage
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Brain volumetric measurements in multiple sclerosis (MS) reflect not only disease-specific processes but also other sources of variability. The latter has to be considered especially in multicenter and longitudinal studies. Here, we compare data generated by three different 3-Tesla magnetic resonance scanners (Philips Achieva; Siemens Verio; GE Signa MR750). ⋯ We conclude that for cross-sectional multicenter studies, the effect of different scanners has to be taken into account. For longitudinal monocentric studies, the expected effect size should exceed the size of false positive findings observed in this study. Assuming a physiological loss of brain volume of about 0.3% per year in healthy adult subjects (Good et al., 2001), which may double in MS (De Stefano et al., 2010; De Stefano et al., 2015), with current tools reliable estimation of brain atrophy in individual patients is only possible over periods of several years.
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Edited MRS allows the detection of low-concentration metabolites, whose signals are not resolved in the MR spectrum. Tailored acquisitions can be designed to detect, for example, the inhibitory neurotransmitter γ-aminobutyric acid (GABA), or the reduction-oxidation (redox) compound glutathione (GSH), and single-voxel edited experiments are generally acquired at a rate of one metabolite-per-experiment. We demonstrate that simultaneous detection of the overlapping signals of GABA and GSH is possible using Hadamard Encoding and Reconstruction of Mega-Edited Spectroscopy (HERMES). ⋯ Hadamard combinations of the four sub-experiments yield GABA and GSH difference spectra. It is shown that HERMES gives excellent separation of the edited GABA and GSH signals in phantoms, and resulting edited lineshapes agree well with separate Mescher-Garwood Point-resolved Spectroscopy (MEGA-PRESS) acquisitions. In vivo, the quality and signal-to-noise ratio (SNR) of HERMES spectra are similar to those of sequentially acquired MEGA-PRESS spectra, with the benefit of saving half the acquisition time.
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The structural heterogeneity of tumor tissue can be probed by diffusion MRI (dMRI) in terms of the variance of apparent diffusivities within a voxel. However, the link between the diffusional variance and the tissue heterogeneity is not well-established. To investigate this link we test the hypothesis that diffusional variance, caused by microscopic anisotropy and isotropic heterogeneity, is associated with variable cell eccentricity and cell density in brain tumors. ⋯ In conclusion, DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density. These results constitute convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI. Decomposing effects of microscopic anisotropy and isotropic heterogeneity facilitates an improved interpretation of tumor heterogeneity as well as diffusion anisotropy on both the microscopic and macroscopic scale.