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Abstract #2973

Sonic DLTM Enhanced 3D Double-Echo Steady-State Sequence for Improved Imaging Resolution in Magnetic Resonance Neurography

Yan Wen1, Darryl B. Sneag2, Sophie Queler2, Maggie Fung1, Xucheng Zhu1, and Ek T. Tan2
1GE HealthCare, Waukesha, WI, United States, 2Hospital for Special Surgery, New York, NY, United States

Synopsis

Keywords: Neurography, MSK

Motivation: High spatial resolution is crucial for MR neurography to accurately depict small peripheral nerves and associated pathology. However, achieving high-resolution images is often constrained by scan time and signal-to-noise ratio (SNR).

Goal(s): This study explores the feasibility of using a deep learning acquisition and reconstruction method for highly accelerated imaging (Sonic DLTM) to improve imaging resolution in a 3D double-echo steady-state sequence (MENSA NERVE).

Approach: The study compares images from reference and proposed sequences in patients undergoing routine upper extremity and neck MR neurography.

Results: Preliminary results indicate that the prototype Sonic DLTM can achieve higher imaging resolution at the same scan time.

Impact: The higher acceleration factors enabled by Sonic DLTM can be utilized to achieve higher spatial resolution in MENSA NERVE, leading to better nerve morphology depiction.

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