Medical College of Wisconsin
CTSICores SearchResearch InformaticsREDCap

Optimization of seed density in DTI tractography for structural networks. J Neurosci Methods 2012 Jan 15;203(1):264-72

Date

10/08/2011

Pubmed ID

21978486

Pubmed Central ID

PMC3500612

DOI

10.1016/j.jneumeth.2011.09.021

Scopus ID

2-s2.0-81555219136 (requires institutional sign-in at Scopus site)   50 Citations

Abstract

Diffusion tensor imaging (DTI) has been used for mapping the structural network of the human brain. The network can be constructed by choosing various brain regions as nodes and fiber tracts connecting those regions as links. The structural network generated from DTI data can be affected by noise in the scans and the choice of tractography algorithm. This study aimed to examine the effect of the number of seeds in tractography on the variance of structural networks. The variance of the network was characterized using an approach similar to the National Electrical Manufacturers Association (NEMA) standards for measurement of image noise. It was shown that the variance of the network is inversely related to the square root of seed density. Consequently, the number of seeds has a large impact on local characteristics and metrics of the network architecture. As the number of seeds increased, increased stability of structural network metrics was observed. However, more seeds can also lead to more spurious fibers and thus affect nodal degrees and edge weights, and proper thresholding may be necessary to create an appropriate weighted network. Because the variance of the network is also influenced by other imaging factors, further increase in the number of seeds has little effect in reducing the network variance. The selection of the seed number should be a balance between the network variance and computational effort.

Author List

Cheng H, Wang Y, Sheng J, Sporns O, Kronenberger WG, Mathews VP, Hummer TA, Saykin AJ

Authors

Vincent Mathews MD Chair, Professor in the Radiology department at Medical College of Wisconsin
Yang Wang MD Professor in the Radiology department at Medical College of Wisconsin




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

Algorithms
Brain
Brain Mapping
Diffusion Tensor Imaging
Humans
Image Processing, Computer-Assisted
Male
Models, Neurological
Models, Theoretical
Nerve Net
Young Adult