Abstract #4800

Personalized DCE-MRI parametric mapping of gynecological cancer using high spatiotemporal resolution GRASP

Nathanael Kim¹, Yousef Mazaheri¹, Yulia Lakhman², Li Feng³, Ersin Bayram⁴, Alberto Vargas², and Ricardo Otazo^1,2

¹Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, ⁴GE Healthcare, Waukesha, WI, United States

Personalized estimation of the arterial input function (AIF) in DCE-MRI has been a relatively challenging task due to the slow imaging speed of conventional MRI. As a consequence, a population AIF is usually employed for parametric mapping, which represents a group effect rather than the long-desired personalized quantification. In this work, we use the GRASP method to perform DCE-MRI of gynecological tumors with high spatial and temporal resolution and to estimate the AIF directly from the data. The personalized AIF shows higher consistency with the tumor enhancement compared to the population AIF.

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