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Abstract #2906

Biexponential modeling of the diffusion weighted MRI signal in a U87 brain tumor model: a comparison of least squares and Bayesian modeling

Alexander D. Cohen 1 , Kimberly R. Pechman 1 , Mona Al-Gizawiy 1 , and Kathleen M. Schmainda 1,2

1 Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2 Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States

The DWI signal deviates from monoexponential behavior at high b-values in tissue. In this study, two techniques were used to fit a biexponential model to this signal: a non-linear least squares approach and a Bayesian approach. Biexponential DWI parameters were compared between fitting techniques and between tumor and normal tissue in a rat U87 brain tumor model. Bayesian modeling proved superior for differentiating tumor from GM. This technique also resulted in qualitatively better-looking maps with enhanced tumor to gray matter contrast compared to the traditionally used least-squares approach. There were also statistically significant differences between modeling techniques for several parameters.

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