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Water Mobility Spectral Imaging of the Spinal Cord: Parametrization of Model-free Laplace MRI

Overview
Publisher Elsevier
Specialty Radiology
Date 2018 Dec 26
PMID 30584915
Citations 14
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Abstract

Diffusion magnetic resonance imaging (dMRI) of biological systems most often results in non-monoexponential signal, due to their complexity and heterogeneity. One approach to interpreting dMRI data without imposing tissue microstructural models is to fit the signal to a multiexponential function, which is sometimes referred to as an inverse Laplace transformation, and to display the coefficients as a distribution of the diffusivities, or water mobility spectra. Until recently, this method has not been used in a voxelwise manner, mainly because of heavy data requirements. With recent advancements in processing and experimental design, voxelwise Laplace MRI approaches are becoming feasible and attractive. The rich spectral information, combined with a three-dimensional image, presents a challenge because it tremendously increases the dimensionality of the data and requires a robust method for interpretation and analysis. In this work, we suggest parameterizing the empirically measured water mobility spectra using a bimodal lognormal function. This approach allows for a compact representation of the spectrum, and it also resolves overlapping spectral peaks, which allows for a robust extraction of their signal fraction. We apply the method on a fixed spinal cord sample and use it to generate robust intensity images of slow- and fast-diffusion components. Using the parametric variables, we create novel image contrasts, among them the information entropy of the water mobility spectrum, which pack unique features of the individual diffusion regimes in the investigated system.

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References
1.
Mulkern R, Zengingonul H, Robertson R, Bogner P, Zou K, Gudbjartsson H . Multi-component apparent diffusion coefficients in human brain: relationship to spin-lattice relaxation. Magn Reson Med. 2000; 44(2):292-300. DOI: 10.1002/1522-2594(200008)44:2<292::aid-mrm17>3.0.co;2-q. View

2.
Niendorf T, Dijkhuizen R, Norris D, van Lookeren Campagne M, Nicolay K . Biexponential diffusion attenuation in various states of brain tissue: implications for diffusion-weighted imaging. Magn Reson Med. 1996; 36(6):847-57. DOI: 10.1002/mrm.1910360607. View

3.
Ronen I, Moeller S, Ugurbil K, Kim D . Analysis of the distribution of diffusion coefficients in cat brain at 9.4 T using the inverse Laplace transformation. Magn Reson Imaging. 2006; 24(1):61-8. DOI: 10.1016/j.mri.2005.10.023. View

4.
Reci A, Sederman A, Gladden L . Obtaining sparse distributions in 2D inverse problems. J Magn Reson. 2017; 281:188-198. DOI: 10.1016/j.jmr.2017.05.010. View

5.
Jones C, Xiang Q, Whittall K, MacKay A . Linear combination of multiecho data: short T2 component selection. Magn Reson Med. 2004; 51(3):495-502. DOI: 10.1002/mrm.10713. View