Advanced White Matter Fiber Tractography Using Non-Gaussian Diffusion MRI


A new white matter tractography method based on the dMRI technique of diffusional kurtosis imaging (DKI) has been developed. This method, known as DKI fiber tractography (DKI-FT), substantially improves upon the existing technique because of its ability to resolve intersecting fiber bundles. Moreover, since it is also easily implemented on clinical scanners, DKI-FT is an attractive alternative for clinical applications.

Overview: White matter fiber tractography (WMFT) refers to a class of techniques that use data obtained with diffusion magnetic resonance imaging (dMRI) to map axonal fiber bundles in brain. Because WMFT can be obtained in three dimensions for in vivo whole brain in a completely noninvasive manner, it has revolutionized the study of structural brain connectivity and is currently being used clinically for the planning of neurosurgical interventions. The various WMFT methods differ in accuracy and practicality. Human applications in clinical settings have favored a method based on diffusion tensor imaging (DTI) (a type of dMRI). The method, called DTI fiber tractography (DTI-FT), is readily implemented on standard clinical MRI scanners, but suffers from substantial inaccuracies as it is incapable of detecting the intersection of two or more fiber bundles within an imaging voxel.

Applications: Brain imaging, neurosurgical planning, assessment of neurological disorders such as Alzheimer’s disease

Advantages: Resolution of intersecting neuronal fiber bundles

Publications: Jenson, Jens, et al. "Leading Non-Gaussian Corrections for Diffusion Orientation Distribution Function."  NMR Biomed. 27(2):202-211, 2014.

Inventors:                       J. Helpern, J. Jenson, A. Tabesh

Patent Status:                US Utility Application Filed 03/31/2015

MUSC-FRD Technology ID: P1440

Patent Information:
For Information, Contact:
Marketing / Licensing Officer
Marketing/Licensing Officer
MUSC Foundation for Research Development
Joseph Helpern
Ali Tabesh (Deceased 9.1.14)
Jens Jenson
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