Abstract #3292

Why You Should Fit Signal Intensity, Not Relaxivity, for Quantitative DCE-MRI

Julie Camille DiCarlo^1,2, Anum S Kazerouni³, and Thomas E Yankeelov^1,2,4,5,6

¹Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, United States, ²Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX, United States, ³Department of Radiology, University of Washington, Seattle, WA, United States, ⁴Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, United States, ⁵Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX, United States, ⁶Department of Oncology, The University of Texas at Austin, Austin, TX, United States

Pharmacokinetic modeling of DCE-MRI is based on fitting perfusion parameters to contrast agent concentration or relaxivity curves computed using the nonlinear spoiled gradient-echo (SPGR) signal equation, T₁ mapping values, and the linear relationship between T₁ and contrast agent relaxivity. The nonlinear term of the SPGR equation has implications for how image noise scales in the concentration. By simulating image noise at different levels for ideal curves of different parameter values, we show why it’s advantageous to fit signal intensity curves rather than relaxivity curves.

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