Abstract #0714

Improving the accuracy of renal perfusion measurements from ASL by using multiple TIs: Validation with DCE MRI

Christopher Charles Conlin^1,2, Yangyang Zhao², and Jeff Lei Zhang^1,3

¹Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, UT, United States, ²Bioengineering, University of Utah, Salt Lake City, UT, United States, ³Radiology, University of Utah School of Medicine, Salt Lake City, UT, United States

This study presents an approach for measuring renal perfusion from multi-TI ASL data and examines the impact of TI-sampling density on perfusion estimation. Our approach incorporates a tracer-kinetic model of the ASL difference signal and a correction for inversion-efficiency artifacts. It was used to measure renal perfusion in human subjects from ASL data sampled at different numbers of TIs and validated against an established DCE-MRI technique. For ASL data sampled at more than two TIs, our approach showed good agreement and correlation with DCE-MRI, demonstrating robust modeling of the ASL difference signal and accurate measurement of renal perfusion.

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