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Detection of acute nervous system injury with advanced diffusion-weighted MRI: a simulation and sensitivity analysis. NMR Biomed 2015 Nov;28(11):1489-506



Pubmed ID




Scopus ID

2-s2.0-84945471406   16 Citations


Diffusion-weighted imaging (DWI) is a powerful tool to investigate the microscopic structure of the central nervous system (CNS). Diffusion tensor imaging (DTI), a common model of the DWI signal, has a demonstrated sensitivity to detect microscopic changes as a result of injury or disease. However, DTI and other similar models have inherent limitations that reduce their specificity for certain pathological features, particularly in tissues with complex fiber arrangements. Methods such as double pulsed field gradient (dPFG) and q-vector magic angle spinning (qMAS) have been proposed to specifically probe the underlying microscopic anisotropy without interference from the macroscopic tissue organization. This is particularly important for the study of acute injury, where abrupt changes in the microscopic morphology of axons and dendrites manifest as focal enlargements known as beading. The purpose of this work was to assess the relative sensitivity of DWI measures to beading in the context of macroscopic fiber organization and edema. Computational simulations of DWI experiments in normal and beaded axons demonstrated that, although DWI models can be highly specific for the simulated pathologies of beading and volume fraction changes in coherent fiber pathways, their sensitivity to a single idealized pathology is considerably reduced in crossing and dispersed fibers. However, dPFG and qMAS have a high sensitivity for beading, even in complex fiber tracts. Moreover, in tissues with coherent arrangements, such as the spinal cord or nerve fibers in which tract orientation is known a priori, a specific dPFG sequence variant decreases the effects of edema and improves specificity for beading. Collectively, the simulation results demonstrate that advanced DWI methods, particularly those which sample diffusion along multiple directions within a single acquisition, have improved sensitivity to acute axonal injury over conventional DTI metrics and hold promise for more informative clinical diagnostic use in CNS injury evaluation.

Author List

Skinner NP, Kurpad SN, Schmit BD, Budde MD


Matthew Budde PhD Associate Professor in the Neurosurgery department at Medical College of Wisconsin
Shekar N. Kurpad MD, PhD Chair, Professor in the Neurosurgery department at Medical College of Wisconsin
Brian Schmit PhD Professor in the Biomedical Engineering department at Marquette University
Nathan Skinner in the CTSI department at Medical College of Wisconsin - CTSI

MESH terms used to index this publication - Major topics in bold

Acute Disease
Computer Simulation
Diffuse Axonal Injury
Diffusion Tensor Imaging
Image Enhancement
Image Interpretation, Computer-Assisted
Models, Neurological
Models, Statistical
Reproducibility of Results
Sensitivity and Specificity
jenkins-FCD Prod-482 91ad8a360b6da540234915ea01ff80e38bfdb40a