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Improved real-time tagged MRI using REALTAG.

Weiyi Chen¹, Nam Gyun Lee², Dani Byrd³

¹Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California.

Magnetic Resonance in Medicine

|December 25, 2019

Summary

A new real-time tagged MRI method, REALTAG, significantly enhances tag persistence and contrast-to-noise ratio for speech imaging. This advancement allows for detailed study of tongue biomechanics during natural speech production.

Keywords:

real-time MRI speech production tag persistence tagged MRI tongue deformation

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Area of Science:

Medical Imaging
Biophysics
Speech Science

Background:

Real-time MRI is crucial for dynamic physiological processes.
Current tagging methods in MRI have limitations in tag persistence and signal quality.
Studying tongue biomechanics during speech requires high temporal and spatial resolution.

Purpose of the Study:

To evaluate a novel real-time tagged MRI technique called REALTAG.
To assess REALTAG's ability to increase tag persistence and improve signal-to-noise ratio for speech imaging.
To demonstrate REALTAG's utility in capturing detailed tongue movements during speech.

Main Methods:

REALTAG employs intermittent tagging during continuous real-time spiral acquisition.
A 180° tagging flip angle and novel phase-sensitive reconstruction are utilized.
Simulations and in vivo evaluations compared REALTAG with conventional tagging (90° flip angle).

Main Results:

REALTAG demonstrated a twofold increase in contrast-to-noise ratio.
Tag persistence was extended by over 1.9-fold, reaching 1150 ms.
High-resolution (2 mm), high-frame-rate (179 frames/s) imaging captured tongue deformation during vowel transitions.

Conclusions:

REALTAG substantially increases tag persistence in real-time MRI.
The method provides a powerful tool for studying tongue biomechanics and articulatory dynamics.
REALTAG enables the capture of complex, longer-duration motion patterns in speech production.