Non-invasive quantitative imaging of selective microstructure-sizes with magnetic resonance

• URL: http://arxiv.org/abs/2006.02035v1
• Date: Wed, 3 Jun 2020 04:15:38 GMT
• Title: Non-invasive quantitative imaging of selective microstructure-sizes with magnetic resonance
• Authors: Milena Capiglioni, Analia Zwick, Pablo Jimenez, Gonzalo A. Alvarez
• Abstract summary: We report on a method that only requires two measurements and its proof-of-principle experiments to produce images of selective microstructure sizes. We design microstructure-size filters with spin-echo sequences that exploit magnetization "decay-shifts" rather than the commonly used decay-rates.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Extracting reliable and quantitative microstructure information of living tissue by non-invasive imaging is an outstanding challenge for understanding disease mechanisms and allowing early stage diagnosis of pathologies. Magnetic Resonance Imaging is the favorite technique to pursue this goal, but still provides resolution of sizes much larger than the relevant microstructure details on in-vivo studies. Monitoring molecular diffusion within tissues, is a promising mechanism to overcome the resolution limits. However, obtaining detailed microstructure information requires the acquisition of tens of images imposing long measurement times and results to be impractical for in-vivo studies. As a step towards solving this outstanding problem, we here report on a method that only requires two measurements and its proof-of-principle experiments to produce images of selective microstructure sizes by suitable dynamical control of nuclear spins with magnetic field gradients. We design microstructure-size filters with spin-echo sequences that exploit magnetization "decay-shifts" rather than the commonly used decay-rates. The outcomes of this approach are quantitative images that can be performed with current technologies, and advance towards unravelling a wealth of diagnostic information based on microstructure parameters that define the composition of biological tissues.

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