Nonuniformities of gradient magnetic fields in diffusion-weighted MRI can introduce systematic errors in estimates of diffusion measures. While there are correction methods that can compensate for these errors, as presented in the Human Connectome Project, such non-linear effects are assumed to be negligible for typical applications and, hence, gradient nonuniformities are mostly left uncorrected. In this work, we evaluated the effect of ignoring such diffusion gradient nonuniformities on measures derived from diffusion tensor imaging. In particular, we simulated deviations from the ground-truth in terms of b-value and diffusion gradient orientation and investigated the resulting bias in fractional anisotropy and orientation of the first eigenvector. Our results demonstrate that not including a correction strategy to mitigate diffusion gradient imperfections especially for high quality data may lead to a significant bias for diffusion measure estimates.
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