Effects of image reconstruction on fiber orientation mapping from multichannel diffusion MRI: reducing the noise floor using SENSE - Sotiropoulos, S.N.; Moeller, S.; Jbabdi, S.; Xu, J.; Andersson, J.L.; Auerbach, E.J.; Yacoub, E.; Feinberg, D.; Setsompop, K.; Wald, L.L.; Behrens, T.E.J.; Ugurbil, K.; et al. (Wiley, 2013)
Purpose: To examine the effects of the reconstruction algorithm of magnitude images from multi-channel diffusion MRI on fibre orientation estimation. Theory and Methods: It is well established that the method used to combine signals from different coil elements in multi-channel MRI can have an impact on the properties of the reconstructed magnitude image. Utilising a root-sum-of-squares (RSoS) approach results in a magnitude signal that follows an effective non-central-distribution. As a result, the noise floor, the minimum measurable in the absence of any true signal, is elevated. This is particularly relevant for diffusion-weighted MRI, where the signal attenuation is of interest. Results: In this study, we illustrate problems that such image reconstruction characteristics may cause in the estimation of fibre orientations, both for model-based and model-free approaches, when modern 32-channel coils are employed. We further propose an alternative image reconstruction method that is based on sensitivity encoding (SENSE) and preserves the Rician nature of the single-channel, magnitude MR signal. We show that for the same k-space data, RSoS can cause excessive overfitting and reduced precision in orientation estimation compared to the SENSE-based approach. Conclusion: These results highlight the importance of choosing the appropriate image reconstruction method for tractography studies that use multi-channel receiver coils for diffusion MRI acquisition.