New Perspectives on the Sources of White Matter DTI Signal

Sharon Peled
IEEE Transactions on Medical Imaging
Volume 26, Number 11, Pages 1448-1455
November, 2007

Download full paper            DOI: 10.1109/TMI.2007.906787

Abstract

A minimalist numerical model of white matter is presented, the objective of which is to help provide a biological basis for improved diffusion tensor imaging (DTI) analysis. Water diffuses, relaxes, and exchanges in three compartments-intracel- lular, extracellular, and myelin sheath. Exchange between com- partments is defined so as to depend on the diffusion coefficients and the compartment sizes. Based on the model, it is proposed that an additive "baseline tensor" that correlates with intraaxonal water volume be included in the computation. Anisotropy and tortuosity calculated from such analysis may correspond better to tract ultrastructure than if calculated without the baseline. According to the model, reduced extracellular volume causes increased baseline and reduced apparent diffusion. Depending on the pulse sequence, reduced permeability can cause an increase in both the baseline and apparent diffusion.

Reference

Peled S. New perspectives on the sources of white matter dti signal. IEEE Transactions on Medical Imaging 2007;26(11):1448-1455.

Bibtex entry

@ARTICLE{peledTMI07,
  author         = {Sharon Peled},                                             
  title          = {New Perspectives on the Sources of White Matter DTI        
                   Signal},                                                    
  journal        = {IEEE Transactions on Medical Imaging},                     
  year           = {2007},                                                     
  volume         = {26},                                                       
  pages          = {1448--1455},                                               
  number         = {11},                                                       
  month          = {November},                                                 
  doi            = "10.1109/TMI.2007.906787"}

Grants

NIH R01-MH074794