期刊
IEEE TRANSACTIONS ON MEDICAL IMAGING
卷 28, 期 7, 页码 1023-1036出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMI.2008.2012113
关键词
Cortical connectivity; cortical network; diffusion-tensor imaging (DTI); Edmonds-Karp algorithm; fiber tracking; link-disjoint paths; magnetic resonance imaging (MRI); shortest path; structural adjacency matrix (SAM); tractography; white matter
类别
资金
- Australian Research Council (ARC) [LX0882154]
- Discovery Project [DP0986320]
- National Health and Medical Research Council C. J. Martin Fellowship [454797]
We arm researchers with a simple method to chart a macroscopic cortico-cortical connectivity network in living human subjects. The researcher provides a diffusion-magnetic resonance imaging (MRI) data set and N cortical regions of interest. In return, we provide an N x N structural adjacency matrix ( A quantifying the relative connectivity between all cortical region pairs. We also return a connectivity map for each pair to enable visualization of interconnecting fiber bundles. The measure of connectivity we devise is: 1) free of length bias, 2) proportional to fiber bundle cross-sectional area, and 3) invariant to an exchange of seed and target. We construct a 3-D lattice scaffolding (graph) for white-matter by drawing a link between each pair of voxels in a 26-voxel neighborhood for which their two respective principal eigenvectors form a sufficiently small angle. The connectivity between a cortical region pair is then measured as the maximum number of link-disjoint paths that can be established between them in the white-matter graph. We devise an efficient Edmonds-Karp-like algorithm to compute a conservative bound on the maximum number of link-disjoint paths. Using both simulated and authentic diffusion-tensor imaging data, we demonstrate that the number of link-disjoint paths as a measure of connectivity satisfies properties 1)-3), unlike the fraction of intersecting streamlines-the measure intrinsic to most existing probabilistic tracking algorithms. Finally, we present connectivity maps of some notoriously difficult to track longitudinal and contralateral fasciculi.
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