Advanced Diffusion MR Tractography for Surgical Planning

  • Jeffrey I. Berman


A goal of neurosurgery is to preserve both functionally important cortices and the underlying white matter tracts. Damage to either portion of a pathway may cause postoperative functional deficit. Diffusion MR tractography remains the only noninvasive method of determining the subcortical course of white matter tracts. Tractography based upon diffusion MR can follow a specific white matter tract from voxel to voxel in 3D through the brain. Diffusion MR tractography complements other surgical mapping techniques which are restricted to the grey matter. However, the quality and clinical utility of diffusion tractography is dependent on the type of MRI acquisition and post-processing algorithm used. Traditional diffusion tensor imaging (DTI) is widely used for surgical planning, but fails to accurately represent the microstructure of crossing white matter tracts. The insufficiencies of DTI have motivated the development of advanced diffusion MR techniques capable of accurately describing the microstructure and connectivity of complex white matter tracts. This chapter describes how advanced diffusion MR improves white matter tract localization and enhances surgical planning.

It is critical that the capabilities and limitations of advanced diffusion MR be understood so the technique can be safely used for surgical planning. The first section of this chapter describes the motivation for translating advanced diffusion MR into a tool for surgical planning. The second section reviews the acquisition and reconstruction of various advanced diffusion MR techniques. The final section describes how high angular resolution diffusion imaging (HARDI) tractography has been translated into a routinely used tool for surgical planning.


Diffusion Tensor Imaging White Matter Tract Axonal Bundle Fiber Tractography Surgical Navigation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Children’s Hospital of Philadelphia, and University of Pennsylvania Perelman School of MedicinePhiladelphiaUSA

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