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The average pathlength map: A diffusion MRI tractography-derived index for studying brain pathology

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dc.contributor.authorPannek, K.
dc.contributor.authorMathias, J.
dc.contributor.authorBigler, E.
dc.contributor.authorBrown, G.
dc.contributor.authorTaylor, J.
dc.contributor.authorRose, S.
dc.date.issued2011
dc.description.abstractMagnetic resonance diffusion tractography provides a powerful tool for the assessment of white matter architecture in vivo. Quantitative tractography metrics, such as streamline length, have successfully been used in the study of brain pathology. To date, these studies have relied on a priori knowledge of which tracts are affected by injury or pathology and manual delineation of regions of interest (ROIs) for use as waypoints in tractography. This limits the analyses to specific tracts under investigation and relies on the accurate and consistent placement of ROIs. We present a fully automated technique for the voxel-wise analysis of streamline length within the entire brain, the Average Pathlength Map (APM). We highlight the precision and reproducibility of voxel-wise average streamline length over time, and assess normal variability of pathlength values in a cohort of 43 healthy participants. Additionally, we demonstrate the utility of this approach by performing voxel-wise comparison between pathlength values obtained from a patient with a severe traumatic brain injury (TBI, Glasgow Coma Scale Score = 7) and those from contROI participants. Our analysis shows that voxel-wise average pathlength values are comparable to fractional anisotropy (FA) in terms of reproducibility and variability. For the TBI patient, we observed a significant reduction in streamline pathlength in the genu of the corpus callosum and its projections into the frontal lobe. This study demonstrates that the average pathlength map can be used for voxel-based analysis of a quantitative tractography metric within the whole brain, removing both the dependence on a priori knowledge of affected pathways and time-consuming manual delineation of ROIs.
dc.description.statementofresponsibilityKerstin Pannek, Jane L. Mathias, Erin D. Bigler, Greg Brown, Jamie D. Taylor, Stephen E. Rose
dc.identifier.citationNeuroImage, 2011; 55(1):133-141
dc.identifier.doi10.1016/j.neuroimage.2010.12.010
dc.identifier.issn1053-8119
dc.identifier.issn1095-9572
dc.identifier.orcidMathias, J. [0000-0001-8957-8594]
dc.identifier.urihttp://hdl.handle.net/2440/67171
dc.language.isoen
dc.publisherAcademic Press Inc Elsevier Science
dc.rightsCopyright © 2010 Elsevier Inc. All rights reserved.
dc.source.urihttps://doi.org/10.1016/j.neuroimage.2010.12.010
dc.subjectMagnetic resonance
dc.subjectDiffusion weighted imaging
dc.subjectHARDI
dc.subjectQuantitative tractography
dc.subjectConstrained spherical deconvolution
dc.titleThe average pathlength map: A diffusion MRI tractography-derived index for studying brain pathology
dc.typeJournal article
pubs.publication-statusPublished

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