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Two-dimensional selective adiabatic pulses.

S Conolly1, J Pauly, D Nishimura

  • 1Department of Electrical Engineering, Stanford University, California 94305.

Magnetic Resonance in Medicine
|April 1, 1992
PubMed
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Researchers developed novel two-dimensional adiabatic pulses for magnetic resonance imaging and spectroscopy. These pulses enable selective magnetization inversion in specific regions, offering robustness against radiofrequency variations and demonstrating feasibility on standard MRI systems.

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Magnetic Resonance Spectroscopy (MRS)
  • Radiofrequency (RF) Pulse Design

Background:

  • Selective excitation is crucial for targeted data acquisition in MRI and MRS.
  • Adiabatic pulses offer robustness against radiofrequency (RF) field inhomogeneities.
  • Existing methods for 2D selective excitation have limitations in robustness and applicability.

Purpose of the Study:

  • To design and validate novel two-dimensional (2D) selective adiabatic pulses.
  • To achieve magnetization inversion within a defined square region in the xy plane.
  • To develop a 2D adiabatic pulse with selective inversion in both frequency and one spatial dimension.

Main Methods:

  • Utilized separable k-space excitation techniques for pulse design.

Related Experiment Videos

  • Developed a 2D selective adiabatic pulse for square region inversion, insensitive to RF variations.
  • Designed a second 2D adiabatic pulse for frequency and single spatial dimension selective inversion.

    • Main Results:

    • Successfully designed 2D selective adiabatic pulses capable of targeted magnetization inversion.
    • Demonstrated insensitivity to RF variations for the square region inversion pulse.
    • Experimental validation confirmed the feasibility of these 2D adiabatic pulses on commercial MRI systems.

    Conclusions:

    • The developed 2D selective adiabatic pulses are effective for targeted excitation in MRI and MRS.
    • These pulses offer improved robustness and applicability compared to conventional methods.
    • The demonstrated feasibility on commercial systems paves the way for their practical implementation.