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Related Experiment Videos

Effects of slice selection and diffusion on T2 measurement.

S T Wong1, M S Roos

  • 1Lawrence Berkeley Laboratory, University of California, Berkeley 94720.

Magnetic Resonance in Medicine
|October 1, 1987
PubMed
Summary

This study identifies slice selection bias in T2 imaging, offering a correction method. Diffusion effects on T2 estimates were found to be negligible in typical spin-warp experiments.

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Biomedical Engineering
  • Medical Physics

Background:

  • Accurate T2 estimates are crucial for quantitative MRI.
  • Slice selection in multislice imaging can introduce systematic errors.
  • Two-echo spin-warp sequences are common for T2 mapping.

Purpose of the Study:

  • To investigate slice selection and diffusion as sources of systematic error in T2 estimates.
  • To develop a method for correcting bias in T2 images caused by slice profile changes.
  • To assess the impact of diffusion on T2 measurements in typical imaging sequences.

Main Methods:

  • Analysis of selective refocusing pulses in multislice, two-echo, spin-warp experiments.
  • Characterization of changes in slice profiles for sequential echoes.
  • Development and application of a bias correction method for T2 images.
  • Evaluation of diffusion effects on T2 estimates.

Main Results:

  • Slice profiles of sequential echoes change shape due to selective refocusing pulses.
  • This change in slice profiles introduces bias into T2 images calculated from two-echo data.
  • A method to correct this bias was successfully developed and presented.
  • The influence of diffusion on T2 images using standard two-echo sequences was determined to be insignificant.

Conclusions:

  • Slice selection is a significant source of systematic error in T2 estimation using two-echo spin-warp MRI.
  • The proposed method effectively corrects for bias introduced by changing slice profiles.
  • Diffusion has a negligible impact on T2 estimates in typical two-echo MRI experiments, simplifying analysis.

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