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Updated: Jan 19, 2026

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Steady-state imaging with inhomogeneous magnetization transfer contrast using multiband radiofrequency pulses
Shaihan J Malik1,2, Rui P A G Teixeira1,2, Daniel J West1,2
1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Purpose:
Inhomogeneous magnetization transfer (ihMT) is an emerging form of MRI contrast that may offer high specificity for myelinated tissue. Existing ihMT and pulsed MT sequences often use separate radiofrequency pulses for saturation and signal excitation. This study investigates the use of nonselective multiband radiofrequency pulses for simultaneous off-resonance saturation and on-resonance excitation specifically for generation of ihMT contrast within rapid steady-state pulse sequences.
Theory And Methods:
A matrix-based signal modeling approach was developed and applied for both balanced steady state free precession and spoiled gradient echo sequences, accounting specifically for multiband pulses. Phantom experiments were performed using a combination of balanced steady state free precession and spoiled gradient echo sequences, and compared with model fits. A human brain imaging exam was performed using balanced steady state free precession sequences to demonstrate the achieved contrast.
Results:
A simple signal model derived assuming instantaneous radiofrequency pulses was shown to agree well with full integration of the governing equations and provided fits to phantom data for materials with strong ihMT contrast (PL161 root mean square error = 0.9%, and hair conditioner root mean square error = 2.4%). In vivo ihMT ratio images showed the expected white matter contrast that has been seen by other ihMT investigations, and the observed ihMT ratios corresponded well with predictions.
Conclusions:
ihMT contrast can be generated by integrating multiband radiofrequency pulses directly into both spoiled gradient echo and balanced steady state free precession sequences, and the presented signal modeling approach can be used to understand the acquired signals.
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