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Multi-parametric T2 * magnetic resonance fingerprinting using variable echo times.

Cory R Wyatt1,2, Travis B Smith1,3, Manoj K Sammi1

  • 1Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR, USA.

NMR in Biomedicine
|July 17, 2018
PubMed
Summary
This summary is machine-generated.

This study enhances magnetic resonance fingerprinting (MRF) to simultaneously measure T1, T2, and T2* relaxation times. This advanced multi-parametric approach improves quantitative imaging for diseases like cancer and neurodegeneration.

Keywords:
relaxometrysampling strategiessusceptibility weighted imaging

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Area of Science:

  • Biomedical Imaging
  • Quantitative MRI
  • Medical Physics

Background:

  • Quantitative imaging biomarkers are crucial for diagnosing diseases like cancer and neurodegenerative disorders.
  • T1, T2, and T2* relaxation times are sensitive to tissue properties and contrast agent effects.
  • Simultaneous multi-parametric mapping can enhance tissue change detection.

Purpose of the Study:

  • To incorporate T2* relaxation into the magnetic resonance fingerprinting (MRF) framework.
  • To develop a novel method for fitting and correcting off-resonance effects in multi-parametric MRF.
  • To evaluate the feasibility and accuracy of the enhanced MRF technique.

Main Methods:

  • Modified MRF framework incorporating variable echo times (TE) to acquire T2* data.
  • Comparison of incremental and golden angle spiral k-space trajectories.
  • Validation using simulated phantom data, agar phantoms, and in vivo brain scans of healthy volunteers.

Main Results:

  • The enhanced MRF method successfully acquired T1, T2, and T2* relaxation time constants simultaneously.
  • Golden angle spiral rotation demonstrated reduced inaccuracy from off-resonance effects.
  • Strong correlations were observed between conventional and MRF-derived relaxation times (T1, T2, T2*) in phantoms and volunteers.

Conclusions:

  • T2* relaxation can be effectively integrated into the MRF framework using variable echo times.
  • The developed method provides accurate multi-parametric quantitative imaging.
  • This technique holds promise for improved disease detection and monitoring in oncology and neurology.