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Abstract #3374

Regional Lung Ventilation Mapping at 0.55T based on Feature Tracking

Yijing Yang1, Ziwei Zhao1, Ye Tian1, Roberta M. Kato2, Sophia X. Cui3, C.-C. Jay Kuo1, and Krishna S. Nayak1
1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 2Children's Hospital of Los Angeles, Los Angeles, CA, United States, 3Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States


Assessment of regional lung ventilation has significant clinical value for the diagnosis and follow-up of pulmonary diseases. High-performance 0.55T systems have provided new opportunities for pulmonary imaging due to prolonged T2* and reduced susceptibility. Here, we describe an image-based regional lung ventilation assessment method based on real-time bSSFP imaging with 0.3s temporal and 1.64x1.64 mm2 spatial resolution, and feature tracking. In healthy adult volunteers, we demonstrate the ability to detect posture-related left-right differences in ventilation, and test-retest repeatability. We detected -5% to 64% regional volume changes throughout the respiratory cycle from end of exhalation to total lung capacity.

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