No abstract

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) can probe tissue biochemistry in vivo with high resolution and sensitivity without requiring exogenous contrast agents. Applying CEST MRI at ultrahigh field provides advantages of increasing spectral resolution and improving sensitivity to metabolites with faster proton exchange rates such as glutamate, a critical neurotransmitter in the brain. Prior magnetic resonance spectroscopy and CEST MRI studies have revealed altered regulation of glutamate in patients with multiple sclerosis (MS). While CEST imaging facilitates new strategies for investigating the pathology underlying this complex and heterogeneous neurological disease, CEST signals are contaminated or diluted by concurrent effects (e.g., semi-solid magnetization transfer (MT) and direct water saturation) and are scaled by the T1 relaxation time of the free water pool which may also be altered in the context of disease. In this study of 20 relapsing-remitting MS patients and age- and sex-matched healthy volunteers, glutamate-weighted CEST data were acquired at 7.0 T. A Lorentzian fitting procedure was used to remove the asymmetric MT contribution from CEST z-spectra, and the apparent exchange-dependent relaxation (AREX) correction was applied using an R1 map derived from an inversion recovery sequence to further isolate glutamate-weighted CEST signals from concurrent effects. Associations between AREX and cognitive function were examined using the Minimal Assessment of Cognitive Function in MS battery. After isolating CEST effects from MT, direct water saturation, and T1 effects, glutamate-weighted AREX contrast remained higher in gray matter than in white matter, though the difference between these tissues decreased. Glutamate-weighted AREX in normal-appearing gray and white matter in MS patients did not differ from healthy gray and white matter but was significantly elevated in white matter lesions. AREX in some cortical regions and in white matter lesions correlated with disability and measures of cognitive function in MS patients. However, further studies with larger sample sizes are needed to confirm these relationships due to potential confounding effects. The application of MT and AREX corrections in this study demonstrates the importance of isolating CEST signals for more specific characterization of the contribution of metabolic changes to tissue pathology and symptoms in MS.

BACKGROUND AND PURPOSE:The purpose of the study is to characterize diffusion tensor imaging indices in the developing spinal cord, evaluating differences based on age and cord region. Describing the progression of DTI indices in the pediatric cord increases our understanding of spinal cord development. MATERIALS AND METHODS:A retrospective analysis was performed on DTI acquired in 121 pediatric patients (mean, 8.6 years; range, 0.3-18.0 years) at Monroe Carell Jr. Children's Hospital at Vanderbilt from 2017 to 2018. Diffusion-weighted images (15 directions; b ϭ 750 s/mm 2 ; slice thickness, 5 mm; in-plane resolution, 1.0 ϫ 1.0 mm 2 ) were acquired on a 3T scanner in the cervicothoracic and/or thoracolumbar cord. Manual whole-cord segmentation was performed. Images were masked and further segmented into cervical, upper thoracic, thoracolumbar, and conus regions. Analyses of covariance were performed for each DTI-derived index to investigate how age affects diffusion across cord regions, and 95% confidence intervals were calculated across age for each derived index and region. Post hoc testing was performed to analyze regional differences. RESULTS:Analyses of covariance revealed significant correlations of age with axial diffusivity, mean diffusivity, and fractional anisotropy (all, P Ͻ .001). There were also significant differences among cord regions for axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy (all, P Ͻ .001). CONCLUSIONS:This research demonstrates that diffusion evolves in the pediatric spinal cord during development, dependent on both cord region and the diffusion index of interest. Future research could investigate how diffusion may be affected by common pediatric spinal pathologies. ABBREVIATIONS: AD ϭ axial diffusivity; ANCOVA ϭ analyses of covariance; DTI ϭ diffusion tensor imaging; EPI ϭ echo planar imaging; FA ϭ fractional anisotropy;FOV ϭ field-of-view; GM ϭ gray matter; MD ϭ mean diffusivity; PMM ϭ population marginal means; RD ϭ radial diffusivity; SNR ϭ signal to noise ratio; WM ϭ white matter