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Abstract #1024

Caveats of non-linear fitting to brain tissue models of diffusion

Ileana O. Jelescu 1 , Jelle Veraart 1 , Els Fieremans 1 , and Dmitry S. Novikov 1

1 Center for Biomedical Imaging, Dept. of Radiology, NYU Langone Medical Center, New York, New York, United States

Compared to DTI, white/gray matter models of diffusion should have improved specificity. However, fit outputs notoriously suffer from bias and poor precision, with most models employing simplifying assumptions to stabilize the fit. Here, we use the example of NODDI to assess the behavior of nonlinear fitting when all model parameters are free. We reveal that the typical full model of brain tissue cannot be reliably determined, due to a duality of solutions, and to the narrow and shallow (boomerang-shaped) minimization landscape. Constraining the fit with fixed parameter values that lack biological validation is not a trustworthy solution to the problem.

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