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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Registered Bioimaging of Nanomaterials for Diagnostic and Therapeutic Monitoring
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Multi-Parametric Molecular Imaging of the Brain Using Optimized Multi-TE Subspace MRSI.

Zepeng Wang, Yahang Li, Chang Cao

    IEEE Transactions on Bio-Medical Engineering
    |January 3, 2024
    PubMed
    Summary

    This study introduces a new multi-echo MR spectroscopic imaging (MRSI) method for detailed brain molecule mapping. The technique offers high-resolution, label-free imaging of metabolites and neurotransmitters, aiding neurological disease research.

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    Area of Science:

    • Neuroimaging
    • Biophysics
    • Biochemistry

    Background:

    • Magnetic Resonance Spectroscopic Imaging (MRSI) is crucial for non-invasive brain analysis.
    • Current MRSI techniques face limitations in resolution, speed, and simultaneous multi-molecule detection.
    • Accurate mapping of metabolites and neurotransmitters is vital for understanding neurological disorders.

    Purpose of the Study:

    • To develop a novel multi-echo MRSI (multi-TE MRSI) approach.
    • Enable label-free, simultaneous, high-resolution mapping of brain molecules and their biophysical parameters.
    • Enhance technological capabilities for multi-parametric molecular imaging.

    Main Methods:

    • Integrated an augmented molecular-component-specific subspace model for multi-TE 1H-MRSI signals.
    • Employed estimation-theoretic experiment optimization for non-uniform TE selection.
    • Utilized physics-driven subspace learning for spatiospectral reconstruction and quantification.
    • Implemented accelerated multi-TE MRSI acquisition for high-resolution data in clinically relevant times.

    Main Results:

    • Optimized TE selection improved estimation of metabolites and neurotransmitters, reducing concentration variance by ~40% and T2 by ~60%.
    • Achieved simultaneous metabolite and neurotransmitter mapping at 3.4 × 3.4 × 6.4 mm 3 resolution.
    • Enabled high-resolution, 3D metabolite T2 mapping for the first time.
    • Demonstrated translational potential by mapping biochemical abnormality in a post-traumatic epilepsy patient.

    Conclusions:

    • Demonstrated feasibility of high-resolution mapping of metabolites, neurotransmitters, and metabolite T2 within clinical time constraints.
    • The method provides richer information for understanding metabolic alterations in neurological diseases.
    • Presents new technological opportunities for neurological applications by uncovering metabolic changes.