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Abstract #1185

5-Minute Quantitative Double-Echo in Steady-State for High-Value Diagnostic Knee MRI: Combining an Efficient Multi-Contrast Acquisition with Quantitative Imaging and Artificial Intelligence

Akshay S Chaudhari1, Murray Grissom2, Zhongnan Fang3, Jin Hyung Lee4, Garry E Gold1, Brian A Hargreaves1, and Kathryn J Stevens1

1Radiology, Stanford University, Palo Alto, CA, United States, 2Radiology, Santa Clara Valley Medical Center, San Jose, CA, United States, 3LVIS Corporation, Palo Alto, CA, United States, 4Neurology, Stanford University, Palo Alto, CA, United States

There exists interest in rapid diagnostic knee magnetic resonance imaging (MRI) protocols in a push towards ‘high-value radiology’. Recent efforts for expediting knee MRI involve accelerating 2D fast spin echo (FSE) sequences, which precludes multiplanar reformations, or using 3D FSE sequences, which can cause image blurring. To overcome these limitations, we show how a 5-minute quantitative double-echo steady-state (qDESS) sequence generates high-resolution and multi-contrast images using deep-learning-based super-resolution, along with automatic T2 relaxation time measurements. In a preliminary study with 25 patients, we demonstrate how qDESS can perform rapid and accurate diagnostic knee MRI using rich structural and quantitative information.

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