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A simple method for mapping the B1 field distribution of linear RF coils
Jan Weis1, Peter Andris, Ivan Frollo
1Department of Radiology, Uppsala University Hospital, SE-751 85, Uppsala, Sweden. jan.weis@radiol.uu.se
Magma (New York, N.Y.)
|December 14, 2005
Summary
A new method accurately measures radio frequency (RF) B1 field components in magnetic resonance imaging (MRI) coils up to 20 MHz. This technique simplifies B1 field mapping for improved image quality and spectral analysis.
Area of Science:
- Medical Physics
- Magnetic Resonance Imaging (MRI)
- Radio Frequency Engineering
Background:
- Inhomogeneity in the radio frequency (RF) B1 field causes significant intensity variations in MRI scans.
- This B1 field inhomogeneity also leads to spatial variations in spectral line amplitudes, affecting quantitative analysis.
- Accurate characterization of the B1 field is crucial for optimizing MRI performance and data interpretation.
Purpose of the Study:
- To present a straightforward method for measuring the B1 field components of an unsegmented linear coil.
- To develop a technique applicable to coils operating at frequencies up to 20 MHz.
- To provide a practical approach for B1 field mapping in MRI systems.
Main Methods:
- The B1 field distribution is modeled as a static magnetic field generated by direct current (DC) flowing through the coil.
- The coil is rotated by 90 degrees to align the measured B1 component with the main static magnetic field (B0).
- Resonance frequency shifts are measured using a spectroscopic imaging sequence to quantify the B1 field.
Main Results:
- Experimental measurements demonstrated good agreement with theoretical calculations.
- The proposed method effectively quantifies B1 field components.
- The technique is validated for linear coils operating up to 20 MHz.
Conclusions:
- The described method offers a simple and effective way to measure B1 field components in linear RF coils.
- This technique can help correct for B1 inhomogeneity, leading to more accurate MRI images and spectral data.
- The findings contribute to improved quantitative MRI and spectral analysis.