Abstract #5637

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach

Satyam Ghodasara¹, Sam Frankel¹, Yong Chen², Mark Griswold³, Nicole Seiberlich³, Vikas Gulani^3,4,5, and Katherine Wright⁴

¹School of Medicine, Case Western Reserve University, Cleveland, OH, United States, ²Biomedical Engineering, University of North Carolina, Chapel Hill, NC, United States, ³Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ⁴Radiology, Case Western Reserve University, Cleveland, OH, United States, ⁵Radiology, University Hospitals, Cleveland, OH, United States

To overcome the shortcomings of curve fitting to quantify perfusion properties, a dictionary matching approach like that used in magnetic resonance fingerprinting is proposed. This dictionary matching approach could be used for any DCE application or model, but is demonstrated and validated here for a dual-input single-compartment model of liver DCE-MRI data. The dictionary matching method provides similar results to the curve fitting method while being simpler to implement and dramatically faster.

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