Abstract #4015

Motion-corrected quantification of cerebral venous oxygenation in vulnerable populations: from neonates to older adults

Yifan Gou¹, Christopher Golden², Zixuan Lin³, Jennifer Shepard², Aylin Tekes³, Zhiyi Hu³, Xin Li³, Kumiko Oishi⁴, Marilyn Albert⁵, Hanzhang Lu³, Peiying Liu^3,6, and Dengrong Jiang³

¹Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States, ²Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ³Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁴Center for Imaging Science, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, United States, ⁵Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁶Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States

Synopsis

Keywords: Oxygenation, OxygenationCerebral venous oxygenation (Y_v) is a biomarker in various brain diseases such as hypoxic-ischemic-encephalopathy in neonates and Alzheimer's disease in the elderly. T₂-Relaxation-Under-Spin-Tagging (TRUST) MRI is a widely used technique to measure global Y_v level. However, subject motion during TRUST scan can cause considerable errors in Y_v quantification. This work developed an automatic algorithm for motion-corrected quantification of Y_v, which showed improved precision of Y_v estimation in both neonates and elderly adults.

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