Magnetic resonance spectroscopic imaging (MRSI) has been widely used for studying metabolic alterations in brain-related pathologies, especially due to its non-invasiveness. Even though some software for MRSI data analysis have been developed, only a few are used by biomedical researchers and in a clinical setting routine, as their use still poses a challenge in keeping the trade-off between information content and ease of implementation. Aiming to increase MRSI analysis automation, our study proposes an open-source toolbox for analysis, automatic spectra quality control and MRSI data visualization. The proposed toolbox allows the visual inspection of all spectra. It makes possible the automated selection of spectra of interest using two different approaches: by clustering them using Pearson’s correlation coefficient or by discarding spectra based on spectral quality metrics. Using the magnetic resonance imaging (MRI) content, the toolbox provides information about the region from which the MRSI grid were acquired, such as the brain tissue ratio in each voxel: white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Once spatial and spectral information is combined, spatial averaging over anatomically defined regions of interest (ROIs) can be applied, for instance, by averaging the spectra and fitting the result. The proposed toolbox aims to simplify and automate MRSI analysis, being easy to install and to use.
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