Keywords: Simulation/Validation, Diffusion/other diffusion imaging techniques, Bayesian Analysis
Motivation: Measurement of ADC in body DWI is typically assumed to be isotropic and therefore the use of single-direction diffusion encoding imaging is commonplace. Estimation of induced bias by this assumption is needed.
Goal(s): To determine whether Bayesian estimation of ADC measurement bias from DTI data suffers from any systematic errors and thus can be used reliably in clinical datasets.
Approach: We use simulation studies over a range of true fractional-anisotopy (FA), signal-to-noise ratio (SNR) and mean-diffusivity parameters, and investigate the accuracy of Bayesian estimation approaches.
Results: Bayesian estimation of ADC bias appears accurate over the range of tested parameters.
Impact: Accurate estimation of ADC bias from single-direction diffusion-encoding schemes is possible using Bayesian approaches in combination with data acquired using a multi-directional diffusion-encoding scheme. This enables pixel-wise estimation of bias and could negate the need for directly acquiring paired datasets.
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