Improved three-dimensional multi-echo gradient echo based myelin water fraction mapping with phase related artifact correction

Lee, Hongpyo; Nam, Yoonho; Lee, Ho‐Joon; Hsu, Jung Jiin; Henry, Roland G.; Kim, Dong Hyun

doi:10.1016/j.neuroimage.2017.11.058

Cited by 27 publications

(48 citation statements)

References 52 publications

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“…The original technique (multi‐spin‐echo based) has been improved by compensating for the stimulated echo effects during the post‐processing estimation . Alternatively, multi‐gradient echo MWI techniques were proposed to compensate for spin‐echo based issues . Deoni et al proposed a quantification of the three main water pools using a more sophisticated biophysical model taking into account inter‐compartments exchanges.…”

Section: Introductionmentioning

confidence: 99%

“…13,14 Alternatively, multi-gradient echo MWI techniques were proposed to compensate for spin-echo based issues. [15][16][17] Deoni et al 18 proposed a quantification of the three main water pools using a more sophisticated biophysical model taking into account inter-compartments exchanges. However, regardless of the model, the MWI techniques still suffer from a lack of consensus and precision.…”

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confidence: 99%

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Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

et al. 2019

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Myelin imaging in the central nervous system is essential for monitoring pathologies involving white matter alterations. Various quantitative MRI protocols relying on the modeling of the interactions of water protons with myelinated tissues have shown sensitivities in case of myelin disruption. Some extracted model parameters are more sensitive to demyelination, such as the bound pool fraction (f) in quantitative magnetization transfer imaging (qMTI), the radial diffusivity in diffusion tensor imaging (DTI), and the myelin water fraction (MWF) in myelin water imaging (MWI). A 3D ultrashort echo time (UTE) sequence within an appropriate water suppression condition (Diff‐UTE) is also considered for the direct visualization of the myelin semi‐solid matrix (Diff‐UTE normalized signal; rSPF). In this paper, we aimed at assessing the sensitivities and correlations of the parameters mentioned above to an immuno‐histological study of the myelin basic protein (MBP) in a murine model of demyelination at 7 T. We demonstrated a high sensitivity of the MRI metrics to demyelination, and strong Spearman correlations in the corpus callosum between histology, macromolecular proton fraction (ρ>0.87) and Diff‐UTE signal (ρ>0.76), but moderate ones with radial diffusivity and MWF (|ρ|<0.70).

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

et al. 2019

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“…This effect can be reduced by B 0 compensation methods. 4,32,36 Recently, a similar study was conducted and reported. 19 However, the results are different from ours.…”

Section: Discussionmentioning

confidence: 87%

“…This phenomenon is due to B 0 inhomogeneity, which progressively affects the signal over TE. This effect can be reduced by B 0 compensation methods …”

Section: Discussionmentioning

confidence: 99%

“…The imaging parameters were as follows: TR = 120 ms, bandwidth = 1560 Hz/pixel, flip angle = 30°, FOV = 256

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256

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88 mm 3 , spatial resolution = 2

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2 mm 3 , matrix size = 128

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128

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44. To test the effect of the range of TEs on the MWF, 80 echoes were acquired with bipolar readout mode, with first TE = 1.6 ms and echo spacing = 1 ms. The last echo was used as a navigator echo to compensate for subject motion .…”

Section: Methodsmentioning

confidence: 99%

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Echo time‐range effects on gradient‐echo based myelin water fraction mapping at 3T

Lee

Nam

Kim

2018

Magnetic Resonance in Med

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Purpose To investigate the effect of the range of TE on multi‐echo gradient echo–based myelin water fraction (MWF) mapping at 3 T. Methods Myelin water fraction estimation was performed using 3 widely used models: magnitude multipool, magnitude 3‐pool, and complex 3‐pool model. Simulations were conducted using a hollow cylinder model with susceptibility anisotropy. The TE range was varied, and its effect on MWF estimation was observed. The same analysis was also performed with in vivo data from 4 healthy volunteers. Results Different MWFs were obtained depending on the range of TE data acquired. In the simulations, the results of both magnitude models had a bias with respect to the true values: a maximum bias of up to 20% for the multipool model, and a maximum bias of up to 8% for the 3‐pool model. This bias was reduced using the complex 3‐pool model (maximum bias was under 2%). These effects were also found in the in vivo data. The MWF values using the complex model was most stable with respect to the TE range. Conclusion The results of the simulation and in vivo data suggest that MWF values fitted using magnitude models are more influenced by the TE range collected for fitting than using the complex model. The complex model is helpful in mitigating bias due to dependencies over the TE range selection.

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So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

Lee

Hyun

Lee

et al. 2020

Magnetic Resonance Imaging

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Myelin water imaging (MWI) is an MRI imaging biomarker for myelin. This method can generate an in vivo whole‐brain myelin water fraction map in approximately 10 minutes. It has been applied in various applications including neurodegenerative disease, neurodevelopmental, and neuroplasticity studies. In this review we start with a brief introduction of myelin biology and discuss the contributions of myelin in conventional MRI contrasts. Then the MRI properties of myelin water and four different MWI methods, which are categorized as T2‐, T2*‐, T1‐, and steady‐state‐based MWI, are summarized. After that, we cover more practical issues such as availability, interpretation, and validation of these methods. To illustrate the utility of MWI as a clinical research tool, MWI studies for two diseases, multiple sclerosis and neuromyelitis optica, are introduced. Additional topics about imaging myelin in gray matter and non‐MWI methods for myelin imaging are also included. Although technical and physiological limitations exist, MWI is a potent surrogate biomarker of myelin that carries valuable and useful information of myelin.Evidence Level: 5Technical Efficacy: 1J. MAGN. RESON. IMAGING 2021;53:360‐373.

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Improved three-dimensional multi-echo gradient echo based myelin water fraction mapping with phase related artifact correction

Cited by 27 publications

References 52 publications

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

Echo time‐range effects on gradient‐echo based myelin water fraction mapping at 3T

So You Want to Image Myelin Using MRI: An Overview and Practical Guide for Myelin Water Imaging

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