SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography

被引:426
|
作者
Smith, Robert E. [1 ]
Tournier, Jacques-Donald [1 ,2 ,3 ,4 ,5 ]
Calamante, Fernando [1 ,2 ,3 ,6 ]
Connelly, Alan [1 ,2 ,3 ,6 ]
机构
[1] Florey Inst Neurosci & Mental Hlth, Imaging Div, Heidelberg, Vic 3084, Australia
[2] Austin Hlth, Dept Med, Melbourne, Vic, Australia
[3] Univ Melbourne, Northern Hlth, Melbourne, Vic, Australia
[4] Kings Coll London, Ctr Developing Brain, London WC2R 2LS, England
[5] Kings Coll London, Div Imaging Sci & Biomed Engn, Dept Biomed Engn, London WC2R 2LS, England
[6] Univ Melbourne, Florey Dept Neurosci & Mental Hlth, Melbourne, Vic, Australia
基金
英国医学研究理事会; 澳大利亚研究理事会;
关键词
Magnetic resonance imaging; Streamlines; Tractography; Diffusion; SIFT; Structural connectivity; CONSTRAINED SPHERICAL DECONVOLUTION; DIFFUSION MRI DATA; SPIN-ECHO; SEGMENTATION; ALGORITHM; REGIONS; IMAGES;
D O I
10.1016/j.neuroimage.2015.06.092
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Diffusion MRI streamlines tractography allows for the investigation of the brain white matter pathways non-invasively. However a fundamental limitation of this technology is its non-quantitative nature, i.e. the density of reconstructed connections is not reflective of the density of underlying white matter fibres. As a solution to this problem, we have previously published the "spherical-deconvolution informed filtering of tractograms (SIFT)" method, which determines a subset of the streamlines reconstruction such that the streamlines densities throughout the white matter are as close as possible to fibre densities estimated using the spherical deconvolution diffusion model; this permits the use of streamline count as a valid biological marker of connection density. Particular aspects of its performance may have however limited its uptake in the diffusion MRI research community. Here we present an alternative to this method, entitled SIFT2, which provides a more logically direct and computationally efficient solution to the streamlines connectivity quantification problem: by determining an appropriate cross-sectional area multiplier for each streamline rather than removing streamlines altogether, biologically accurate measures of fibre connectivity are obtained whilst making use of the complete streamlines reconstruction. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:338 / 351
页数:14
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