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Related Experiment Video

Updated: Mar 30, 2026

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
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Fast myelin water fraction estimation using 2D multislice CPMG.

Alireza Akhondi-Asl1, Onur Afacan2, Mukund Balasubramanian2

  • 1Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA. Alireza.Akhondi-asl@childrens.harvard.edu.

Magnetic Resonance in Medicine
|November 5, 2015
PubMed
Summary

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An MRI Atlas of the Human Fetal Brain: Reference and Segmentation Tools for Fetal Brain MRI Analysis.

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Comparison of dynamic contrast-enhanced MRI versus MAG-3 scintigraphy for differential renal function assessment in pediatric patients.

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Combined prospective and retrospective motion correction for high-resolution linescan acquisitions in the human cerebral cortex at 7T.

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This study introduces a faster MRI method for myelin water fraction mapping, improving accuracy by using Bloch equations and advanced T2 distribution modeling for reliable whole-brain imaging.

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Neuroimaging
  • Biophysics

Background:

  • Conventional T2 relaxometry for myelin water fraction mapping relies on multiexponential fitting, which suffers from long acquisition times and unrealistic models.
  • Limitations include slow imaging and physically implausible T2 distribution assumptions.

Purpose of the Study:

  • To present a novel framework for myelin imaging that significantly enhances imaging speed and the accuracy of myelin water fraction estimation.
  • To overcome the limitations of existing MRI techniques for myelin water mapping.

Main Methods:

  • Employed a 2D multislice Carr-Purcell-Meiboom-Gill sequence for increased volume coverage.
  • Numerically solved Bloch equations to model slice profiles and T2 distributions, using a finite mixture of continuous parametric distributions.
Keywords:
Bloch equationsCarr-Purcell-Meiboom-GillT2 relaxometrymyelin imagingvariable projection

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  • Utilized constrained variable projection optimization for myelin water fraction estimation, validated with synthetic, phantom, and in vivo data.

    • Main Results:

    • The Bloch equation-based model accurately represents slice profiles and T2 signal decay.
    • The proposed method achieved higher myelin water fraction estimation accuracy compared to the nonnegative least squares algorithm.

    Conclusions:

    • The developed framework enables reliable whole-brain myelin imaging.
    • Achieved a resolution of 2×2×4 mm³ in approximately 17 minutes, demonstrating substantial improvements in speed and efficiency.