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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