Abstract
PurposeAn emerging topic in diffusion magnetic resonance is imaging blood microcirculation alongside water diffusion using the intravoxel incoherent motion (IVIM) model. Recently, a combined IVIM diffusion tensor imaging (IVIM‐DTI) model was proposed, which accounts for both anisotropic pseudo‐diffusion due to blood microcirculation and anisotropic diffusion due to tissue microstructures. In this article, we propose a robust IVIM‐DTI approach for simultaneous diffusion and pseudo‐diffusion tensor imaging.MethodsConventional IVIM estimation methods can be broadly divided into two‐step (diffusion and pseudo‐diffusion estimated separately) and one‐step (diffusion and pseudo‐diffusion estimated simultaneously) methods. Here, both methods were applied on the IVIM‐DTI model. An improved one‐step method based on damped Gauss–Newton algorithm and a Gaussian prior for the model parameters was also introduced. The sensitivities of these methods to different parameter initializations were tested with realistic in silico simulations and experimental in vivo data.ResultsThe one‐step damped Gauss–Newton method with a Gaussian prior was less sensitive to noise and the choice of initial parameters and delivered more accurate estimates of IVIM‐DTI parameters compared to the other methods.ConclusionOne‐step estimation using damped Gauss–Newton and a Gaussian prior is a robust method for simultaneous diffusion and pseudo‐diffusion tensor imaging using IVIM‐DTI model. Magn Reson Med 79:2367–2378, 2018. © 2017 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.
Highlights
Diffusion magnetic resonance imaging is a technique that allows mapping of water molecules’ movement due to diffusion in biological tissues, in vivo and noninvasively
This model was shown to be extremely useful for providing meaningful bio-markers such as mean diffusivity (MD) and fractional anisotropy (FA), that are widely used as measures of microstructural tissue changes [6]
It is known that One-step method (OSM) estimation is sensitive to the choice of initial-values [17]
Summary
Diffusion magnetic resonance imaging (dMRI) is a technique that allows mapping of water molecules’ movement due to diffusion in biological tissues, in vivo and noninvasively. With proper modeling techniques, dMRI is capable of capturing several microstructural features and information related to the tissue constituents. There exists several modeling techniques in the literature capable of capturing such information [2,3,4], of which the diffusion tensor imaging (DTI) is the most commonly used. In DTI, water diffusion within a voxel is represented with a rank-2 tensor [5]. Simplistic, this model was shown to be extremely useful for providing meaningful bio-markers such as mean diffusivity (MD) and fractional anisotropy (FA), that are widely used as measures of microstructural tissue changes [6]. DTI is useful for the analysis of neuronal fiber pathways and their visualization (tractography) [7]
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