期刊
NATURE REVIEWS PHYSICS
卷 3, 期 8, 页码 570-588出版社
NATURE PORTFOLIO
DOI: 10.1038/s42254-021-00326-1
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资金
- European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013)/ERC grant [616905]
- European Union's Horizon 2020 research and innovation programme [681094]
- Federal Ministry of Education and Research (BMBF) in the framework of ERA-NET NEURON [01EW1711A]
- Swedish Research Council [NT 2014-6193]
- ERA-NET NEURON (hMRIofSCI)
- BMBF [01EW1711A]
- German Research Foundation (DFG) [2041, AL 1156/2-1, GE 2967/1-1, MO 2397/5-1, MO 2249/3-1]
- DFG Emmy Noether Stipend [MO 2397/4-1]
Quantitative magnetic resonance imaging and in vivo histology aim to characterize tissue microstructure of living brain, providing deeper understanding of MRI tissue contrast and more accurate image parameters as compared to traditional histology methods.
Quantitative magnetic resonance imaging (qMRI) goes beyond conventional MRI, which aims primarily at local image contrast. It provides specific physical parameters related to the nuclear spin of protons in water, such as relaxation times. These parameters carry information about the local microstructural environment of the protons (such as myelin in the brain). Non-invasive in vivo histology using MRI (hMRI) aims to use this information to directly characterize biological tissue microstructure, partially replacing or complementing classical invasive histology. The understanding of MRI tissue contrast provided by hMRI is, in turn, crucial for further improvements of qMRI, and they should be considered closely interlinked. We discuss concepts, models and validation approaches, pointing out challenges and the latest advances in this field. Further, we point out links to physics, including computational and analytical approaches and developments in materials science and photonics, that aid in reference data acquisition and model validation. Quantitative magnetic resonance imaging and in vivo histology go beyond standard magnetic resonance imaging, aiming at characterizing tissue microstructure of the living brain. This Technical Review discusses advances in concepts, instrumentation, biophysical models and validation approaches facilitating this rapidly developing field.
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