title: Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging.
abstract: Diffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized.
  
  
  
  Here we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities.
  
  
  
  Performed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF.
  
  
  
  In this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. Magn Reson Med 76:1837-1847, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
authors.affiliation: NATBRAINLAB, Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Lacerda
authors.affiliation: GE Global Research, Munich, BY, Germany.
authors.forename: Jonathan I
authors.initials: JI
authors.lastname: Sperl
authors.affiliation: GE Global Research, Munich, BY, Germany.
authors.forename: Marion I
authors.initials: MI
authors.lastname: Menzel
authors.affiliation: GE Global Research, Munich, BY, Germany.
authors.forename: Tim
authors.initials: T
authors.lastname: Sprenger
authors.affiliation: Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
authors.forename: Gareth J
authors.initials: GJ
authors.lastname: Barker
authors.affiliation: NATBRAINLAB, Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
authors.forename: Flavio
authors.initials: F
authors.lastname: Dell'Acqua
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D004058:Diffusion; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D066127:White Matter / Q000033:anatomy & histology*
keywords: DSI; ODF; aliasing; diffusion; propagator; resolution