Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous noninvasive acquisition of MR spectra from multiple spatial locations inside the brain. Although H-MRSI is increasingly used in the human brain, it is not yet widely applied in the preclinical setting, mostly because of difficulties specifically related to very small nominal voxel size in the rat brain and low concentration of brain metabolites, resulting in low signal-to-noise ratio (SNR). In this context, we implemented a free induction decay H-MRSI sequence (H-FID-MRSI) in the rat brain at 14.
View Article and Find Full Text PDFMetabolite concentration estimates from magnetic resonance spectroscopy (MRS) are typically quantified using water referencing, correcting for relaxation-time differences between metabolites and water. One common approach is to correct the reference signal for differential relaxation within three tissue compartments (gray matter, white matter, and cerebrospinal fluid) using fixed literature values. However, water relaxation times (T and T) vary between brain locations and with age.
View Article and Find Full Text PDFPurpose: Relaxation correction is crucial for accurately estimating metabolite concentrations measured using in vivo MRS. However, the majority of MRS quantification routines assume that relaxation values remain constant across the lifespan, despite prior evidence of T changes with aging for multiple of the major metabolites. Here, we comprehensively investigate correlations between T and age in a large, multi-site cohort.
View Article and Find Full Text PDFPurpose: Metabolite amplitude estimates derived from linear combination modeling of MR spectra depend upon the precise list of constituent metabolite basis functions used (the "basis set"). The absence of clear consensus on the "ideal" composition or objective criteria to determine the suitability of a particular basis set contributes to the poor reproducibility of MRS. In this proof-of-concept study, we demonstrate a novel, data-driven approach for deciding the basis-set composition using Bayesian information criteria (BIC).
View Article and Find Full Text PDFPurpose: Relaxometry, specifically and mapping, has become an essential technique for assessing the properties of biological tissues related to various physiological and pathological conditions. Many techniques are being used to estimate and relaxation times, ranging from the traditional inversion or saturation recovery and spin-echo sequences to more advanced methods. Choosing the appropriate method for a specific application is critical since the precision and accuracy of and measurements are influenced by a variety of factors including the pulse sequence and its parameters, the inherent properties of the tissue being examined, the MRI hardware, and the image reconstruction.
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