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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Fat-Water Phantoms for Magnetic Resonance Imaging Validation: A Flexible and Scalable Protocol
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A structural tissue water fraction phantom derived from electron microscopy for simulation-based evaluation in MRI.

Ryuji Ohshiro1, Yuki Kanazawa2,3, Akihiro Haga4

  • 1Department of Radiology, Bellland General Hospital, Sakai, Japan.

Magma (New York, N.Y.)
|March 26, 2026
PubMed
Summary

This study developed an electron microscopy-derived phantom to accurately measure myelin water fraction (MWF) in MRI. This tool helps standardize quantitative MRI methods for demyelinating diseases.

Keywords:
MRI simulatorMyelin water fraction (MWF)Non-negative least squares (NNLS)Numerical phantomTissue water fraction

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Area of Science:

  • Neuroimaging
  • Biophysics
  • Quantitative MRI

Background:

  • Myelin water fraction (MWF) quantification is crucial for demyelinating disease research.
  • Existing MWF measurements vary due to acquisition parameters and field inhomogeneities.
  • A lack of standardized phantoms with known structural references limits reproducibility.

Purpose of the Study:

  • To develop a novel numerical MRI phantom using electron microscopy (EM) data.
  • To represent structural tissue water fractions for accurate MWF estimation.
  • To evaluate the influence of acquisition and field conditions on simulated MWF.

Main Methods:

  • EM images of CNS tissue were segmented into myelin, axons, and water compartments.
  • Relaxation times were assigned, and simulated MWF was calculated using non-negative least squares.
  • Multi-echo spoiled gradient echo signals were simulated under varying acquisition and field conditions.

Main Results:

  • The EM-derived phantom generated compartment-specific decay curves.
  • Simulated MWF was sensitive to flip angle, TR, and B0/B1 inhomogeneity.
  • The framework visualized compartment mixing and sensitivity to relaxation and field variations.

Conclusions:

  • The developed phantom offers a structural ground truth for reproducible MWF evaluation.
  • This approach aids in optimizing quantitative MRI methods.
  • It supports the standardization of future quantitative MRI methodologies for demyelinating diseases.