Advanced Signal-processing for Ultra-Fast Magnetic Resonance Spectroscopic Imaging, and Training (FAST)

  • Cabañas Egaña, Miquel (Principal Investigator)

    Project Details

    Description

    Magnetic Resonance Spectroscopic Imaging MRSI is an emerging, non-invasive modality of Molecular Imaging that opens the way to in vivo mapping of metabolism. It will greatly contribute to combating major diseases (cancer, Alzheimer's disease, multiple sclerosis, etc), monitoring therapy, drug development. Spin-offs: food inspection, materials research. Till today, major obstacles to routine clinical applications of MRSI are 1) Long measurement time, several minutes minimal, 2) Low spatial resolution and low signal-to-noise ratio of metabolic images, 3) Considerable complexity of MRSI processing, analysis, and data visualization, 4) Sparseness of training facilities. Exploiting the strong synergy between signal processing and MR methodology, this proposal aims to pave the way to real-time MRSI. This involves " Cutting-edge MRSI signal-processing algorithms for quantitation and imaging of metabolites. This includes A Virtual Scanner based on Quantum Mechanics Advanced Semiparametric Estimation Innovative Graphical User-Interfacing " Ultra-fast Data Acquisition at the forefront of MR-methodology. " Innovative e-Training/ToK for young researchers and experts. FAST will contribute to establishing MRSI as non-invasive routine tool in the clinic for combating major diseases. An ultimate goal is MRSI during surgery. An innovative graphical user-interface with web-collaboration will enable interactive communication sessions, with data- and action-sharing, between multiple users. FAST is interdisciplinary and intersectorial and lends itself very well for Training/ToK in all facets of MRSI, with advanced interactive web-based and traditional methods. Partner expertise ranges from medicine to theoretical physics, via biochemistry, chemistry, physics, signal processing, informatics, numerical algebra, and encompasses four Industries. Our joint effort will make MRSI a reliable, ultra-fast, non-invasive, metabolite monitor for the clinic.
    StatusFinished
    Effective start/end date1/12/0630/11/10

    Collaborative partners

    • Université Claude Bernard Lyon 1 (lead)
    • Alter Systems
    • École Polytechnique Federale de Lausanne
    • Institute for Language and Speech Processing
    • Catholic University of Louvain
    • Philips Medical Systems
    • Sanofi-Syntelabo
    • Siemens AG, Medizinische Technik
    • Stichting Katholieke Universiteit
    • Technological Educational Institute of Chaldika
    • University of Manchester
    • Universität Leipzig
    • Ustav Pistrojove Techniky, Akademie vd Eske Republiky

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