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Abstract #1030

SUBSTITUTING GADOLINIUM IN BRAIN MRI USING DEEPCONTRAST: A PROOF-OF-CONCEPT STUDY IN MICE

Haoran Sun1, Xueqing Liu1, Xinyang Feng1, Chen Liu2, Nanyan Zhu3, Sabrina Josefina Gjerswold-Selleck1, Hong-Jian Wei4,5, Pavan Shankar Upadhyayula5,6, Angeliki Mela5,6, Cheng-Chia Wu4,5, Peter Canoll5,6, Andrew F. Laine1, John Thomas Vaughan1, Scott A. Small7,8,9, and Jia Guo7,10
1Department of Biomedical Engineering, Columbia University, New York, NY, United States, 2Department of Electrical Engineering, Columbia University, New York, NY, United States, 3Department of Biological Science, Columbia University, New York, NY, United States, 4Department of Radiation Oncology, Columbia University, New York, NY, United States, 5Columbia University Irving Medical Center, Columbia University, New York, NY, United States, 6Department of Pathology and Cell Biology, Columbia University, New York, NY, United States, 7Department of Psychiatry, Columbia University, New York, NY, United States, 8Departments of Neurology, Columbia University, New York, NY, United States, 9Departments of Radiology, Columbia University, New York, NY, United States, 10Mortimer B. Zickerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States

Cerebral blood volume (CBV) is a hemodynamic correlate of oxygen metabolism and reflects brain activity and function. High-resolution CBV maps can be generated using the steady-state gadolinium-enhanced MRI technique. Recent studies suggest that the exogenous gadolinium based contrast agent (GBCA) can accumulate in the brain after frequent use. Here, we develop and optimize a deep learning algorithm, DeepContrast, which performs equally well as exogenous GBCA in mapping CBV of the normal brain tissue and enhancing glioblastoma. Together, these studies validate our hypothesis that a deep learning approach can potentially replace the need for GBCAs in brain MRI.

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