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Improved estimation of myelin water fraction using complex model fitting.

Yoonho Nam1, Jongho Lee2, Dosik Hwang3

  • 1Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of Korea.

Neuroimage
|April 11, 2015
PubMed
Summary

Gradient echo imaging of white matter myelin water requires complex-valued models. A new complex model fitting approach, applied to complex data without background phase removal, demonstrated the most stable myelin water signal estimation.

Keywords:
B(0) field inhomogeneityFiber orientationFrequency offsetMyelin waterT(2)(⁎) relaxationWhite matter

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Area of Science:

  • Magnetic Resonance Imaging
  • Neuroimaging
  • Biophysics

Background:

  • Gradient echo (GRE) imaging reveals frequency shifts in white matter water compartments (myelin, axonal, extracellular).
  • These shifts depend on fiber orientation and the B0 field, suggesting complex-valued signal models for GRE-based myelin water imaging.

Purpose of the Study:

  • To investigate the reliability of different signal models and fitting approaches for myelin water imaging in GRE.
  • To compare magnitude and complex models fitted to magnitude or complex data.

Main Methods:

  • Evaluated three signal models: magnitude model (magnitude data), complex model (magnitude data), and complex model (complex data).
  • Proposed a novel fitting approach for the complex model using complex data, eliminating the need for background phase removal.

Main Results:

  • The complex model fitted to complex data, using the new approach, yielded the most stable parameter estimation.
  • Comparison revealed superior reliability of the complex model fitting to complex data.

Conclusions:

  • Complex-valued signal modeling is essential for accurate GRE-based myelin water imaging.
  • The proposed complex model fitting approach offers enhanced stability and reliability in myelin water quantification.