title: Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast.
abstract: This project aims to characterize the impact of underlying noise distributions on diffusion-weighted imaging. The noise floor is a well-known problem for traditional magnitude-based diffusion-weighted MRI (dMRI) data, leading to biased diffusion model fits and inaccurate signal averaging. Here, we introduce a total-variation-based algorithm to eliminate shot-to-shot phase variations of complex-valued diffusion data with the intention to extract real-valued dMRI datasets. The obtained real-valued diffusion data are no longer superimposed by a noise floor but instead by a zero-mean Gaussian noise distribution, yielding dMRI data without signal bias. We acquired high-resolution dMRI data with strong diffusion weighting and, thus, low signal-to-noise ratio. Both the extracted real-valued and traditional magnitude data were compared regarding signal averaging, diffusion model fitting and accuracy in resolving crossing fibers. Our results clearly indicate that real-valued diffusion data enables idealized conditions for signal averaging. Furthermore, the proposed method enables unbiased use of widely employed linear least squares estimators for model fitting and demonstrates an increased sensitivity to detect secondary fiber directions with reduced angular error. The use of phase-corrected, real-valued data for dMRI will therefore help to clear the way for more detailed and accurate studies of white matter microstructure and structural connectivity on a fine scale.
authors.affiliation: Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. Electronic address: ceichner@nmr.mgh.harvard.edu.
authors.forename: Cornelius
authors.initials: C
authors.lastname: Eichner
authors.affiliation: Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA.
authors.forename: Stephen F
authors.initials: SF
authors.lastname: Cauley
authors.affiliation: École Polytechnique, University of Montreal, Montréal, Canada.
authors.forename: Julien
authors.initials: J
authors.lastname: Cohen-Adad
authors.affiliation: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
authors.forename: Harald E
authors.initials: HE
authors.lastname: Möller
authors.affiliation: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
authors.forename: Robert
authors.initials: R
authors.lastname: Turner
authors.affiliation: Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA. Electronic address: kawin@nmr.mgh.harvard.edu.
authors.forename: Kawin
authors.initials: K
authors.lastname: Setsompop
authors.affiliation: Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA.
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Wald
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology; D004058:Diffusion; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio