Microscopic fractional anisotropy (μFA) estimation using diffusion MRI is a promising new method for quantifying microstructure, diagnosing pathologies, and measuring brain development. In order for μFA to be a useful metric in clinical and neuroscientific research, its robustness to noise has to be properly understood. In this study, precision of μFA estimation was quantified for different noise levels using propagation of error calculations, simulations, and imaging experiments. We show that μFA is non-linearly sensitive to noise, being the most instable at low values of mean diffusivity (MD) and μFA, and that increasing accuracy by correcting for higher order effects results in decreased precision.
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