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Abstract #2724

Data-driven regularized inversion (DRI) for improved QSM+qBOLD based CMRO2 Mapping: a feasibility study in healthy subjects and ischemic stroke patients

Junghun Cho1, Shun Zhang2, Youngwook Kee3, Pascal Spincemaille3, Thanh Nguyen3, Simon Hubertus4, Ajay Gupta3, and Yi Wang1,3

1Biomedical Engineering, Cornell University, Ithaca, NY, United States, 2Radiology, Tongji Hospital, Wuhan, China, 3Radiology, Weill Cornell Medical College, New York, NY, United States, 4Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany

We propose the use of machine-learning to improve the accuracy of a QSM+qBOLD model based Cerebral metabolic rate of oxygen (CMRO2) and oxygen extraction fraction (OEF) mapping. The proposed method, data-driven regularized inversion or DRI, significantly outperformed, in simulation, the current method at all SNR levels. In n=11 healthy subjects, uniform OEF maps were obtained as expected. In n=18 ischemic stroke patients, low OEF regions were clearly located within the lesion region as defined by DWI.

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