Oryx-MRSI

Oryx-MRSI processes raw 1H-MRSI data in MATLAB to perform spectral fitting with LCModel outputs, chemical shift correction, tissue-fraction calculation, automatic spectral quality control, visualization, and generation of NIfTI metabolite maps registered to the MNI152 atlas for region-specific brain metabolic analysis.

Key Features:

• MATLAB-Based Framework: Built in MATLAB for data processing and analysis of 1H-MRSI datasets.
• Spectral Fitting and LCModel Integration: Integrates LCModel outputs for metabolite quantification and downstream analysis.
• Visualization: Visualizes raw 1H-MRSI data and LCModel output spectra and results.
• Chemical Shift Correction: Implements algorithms to correct chemical shift artifacts in spectral data.
• Tissue Fraction Calculation: Calculates tissue fractions to account for heterogeneous brain tissue composition.
• Metabolite Map Production: Generates detailed metabolite maps for integration with other MRI modalities.
• Automatic Spectral Quality Control: Automatically assesses and controls spectral quality across datasets.
• Registration to Standard Brain Atlas: Registers metabolite maps to the MNI152 brain atlas for spatial normalization.
• Region of Interest (ROI) Analysis: Supports ROI analysis at predefined parcellations on the MNI152 atlas.
• Data Storage: Stores generated metabolite maps in NIfTI format.

Scientific Applications:

• Noninvasive Brain Metabolism Assessment: Enables quantitative evaluation of regional brain metabolites from 1H-MRSI data.
• Neurodegenerative Disease Research: Supports regional metabolite mapping studies of neurodegenerative disorders.
• Brain Tumor Research: Facilitates metabolic characterization and mapping of brain tumors.
• Metabolic Disorder Studies: Enables investigation of brain metabolic disorders through spatially resolved metabolite quantification.
• Multimodal Neuroimaging Integration: Facilitates integration of metabolite maps with other MRI modalities for comprehensive studies.

Methodology:

Computational steps explicitly include import and preprocessing of raw 1H-MRSI to correct artifacts; integration of LCModel outputs for spectral fitting and automatic spectral quality control; chemical shift correction and tissue-fraction calculation; generation and storage of metabolite maps in NIfTI format; spatial normalization of maps to the MNI152 atlas; ROI analysis at predefined parcellations; and visualization of raw data and LCModel outputs.