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Abstract #0441

Improved spiral dynamic MRI of vocal tract shaping at 3 Tesla using dynamic off resonance artifact correction

Sajan Goud Lingala1, Yongwan Lim2, Stanley Kruger3, and Krishna Nayak2

1Biomedical Engineering, University of Iowa, Iowa city, IA, United States, 2Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 3Department of Radiology, University of Iowa, Iowa city, IA, United States

Spiral trajectories have been valuable in several dynamic speech production MRI studies due to its robust motion encoding, and time acquisition efficiency. However they are challenged by off-resonance artifacts at high field strengths and use of long readouts. In this work, we demonstrate correction of off-resonance induced blurring and signal losses on 3T spiral dynamic speech MRI data. The approach estimates the dynamic field map directly from the single TE data and compensates for this during a multi-frequency interpolation reconstruction. Effectiveness in improving sharpness of various articulator boundaries for long readout sequences (> 2ms) are demonstrated.

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