Abstract #0148

Deep Learning Enables A Half Z-spectrum Sampling-based B0 Inhomogeneity Correction for CEST MRI

Yiran Li¹, Danfeng Xie¹, Dushyant Kumar², Abigail Cember², Ravi Prakash Reddy Nanga², Hari Hariharan², John A. Detre³, Ravinder Reddy², and Ze Wang¹

¹Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, ²Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States, ³Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States

This study presents a DL based framework for correcting B0 inhomogeneity for GluCEST imaging using fewer acquisitions. Based on 3 or 5 positive offset CEST images, the proposed method can save >80% of CEST imaging acquisition time as compared to current 26 pairs of double site z-spectrum irradiations based protocol. This approach can be applied to other CEST imaging as well.

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