Human cortical connectome reconstruction from diffusion weighted MRI: The effect of tractography algorithm

Research output: Contribution to journalArticleAcademicpeer-review

73 Citations (Scopus)

Abstract

Reconstructing the macroscopic human cortical connectome by Diffusion Weighted Imaging (DWI) is a challenging research topic that has recently gained a lot of attention. In the present work, we investigate the effects of intra-voxel fiber direction modeling and tractography algorithm on derived structural network indices (e.g. density, small-worldness and global efficiency). The investigation is centered on three semi-independent distinctions within the large set of available diffusion models and tractography methods: i) single fiber direction versus multiple directions in the intra-voxel diffusion model, ii) deterministic versus probabilistic tractography and iii) local versus global measure-of-fit of the reconstructed fiber trajectories. The effect of algorithm and parameter choice has two components. First, there is the large effect of tractography algorithm and parameters on global network density, which is known to strongly affect graph indices. Second, and more importantly, there are remaining effects on graph indices which range in the tens of percent even when global density is controlled for. This is crucial for the sensitivity of any human structural network study and for the validity of study comparisons. We then investigate the effect in choices in tractography algorithm on sensitivity and specificity of the resulting connections with a connectome dissection quality control (QC) approach. In this approach, evaluation of Tract Specific Density Coefficients (TSDCs) measures sensitivity while careful inspection of tractography path results assesses specificity. We use this to discuss interactions in the combined effects of these methods and implications for future studies.
Original languageEnglish
Pages (from-to)1732-1749
Number of pages18
JournalNeuroimage
Volume62
Issue number3
DOIs
Publication statusPublished - Sep 2012

Keywords

  • Diffusion weighted magnetic resonance
  • imaging
  • Tractography
  • Human connectome
  • Structural network analysis
  • Quality control
  • Tract specific density coefficient
  • PROBABILISTIC FIBER TRACKING
  • LIVING HUMAN BRAIN
  • TENSOR MRI
  • SPHERICAL DECONVOLUTION
  • CROSSING FIBERS
  • RESOLUTION
  • MATTER
  • CONNECTIVITY
  • NETWORKS
  • ARCHITECTURE

Cite this

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title = "Human cortical connectome reconstruction from diffusion weighted MRI: The effect of tractography algorithm",
abstract = "Reconstructing the macroscopic human cortical connectome by Diffusion Weighted Imaging (DWI) is a challenging research topic that has recently gained a lot of attention. In the present work, we investigate the effects of intra-voxel fiber direction modeling and tractography algorithm on derived structural network indices (e.g. density, small-worldness and global efficiency). The investigation is centered on three semi-independent distinctions within the large set of available diffusion models and tractography methods: i) single fiber direction versus multiple directions in the intra-voxel diffusion model, ii) deterministic versus probabilistic tractography and iii) local versus global measure-of-fit of the reconstructed fiber trajectories. The effect of algorithm and parameter choice has two components. First, there is the large effect of tractography algorithm and parameters on global network density, which is known to strongly affect graph indices. Second, and more importantly, there are remaining effects on graph indices which range in the tens of percent even when global density is controlled for. This is crucial for the sensitivity of any human structural network study and for the validity of study comparisons. We then investigate the effect in choices in tractography algorithm on sensitivity and specificity of the resulting connections with a connectome dissection quality control (QC) approach. In this approach, evaluation of Tract Specific Density Coefficients (TSDCs) measures sensitivity while careful inspection of tractography path results assesses specificity. We use this to discuss interactions in the combined effects of these methods and implications for future studies.",
keywords = "Diffusion weighted magnetic resonance, imaging, Tractography, Human connectome, Structural network analysis, Quality control, Tract specific density coefficient, PROBABILISTIC FIBER TRACKING, LIVING HUMAN BRAIN, TENSOR MRI, SPHERICAL DECONVOLUTION, CROSSING FIBERS, RESOLUTION, MATTER, CONNECTIVITY, NETWORKS, ARCHITECTURE",
author = "M. Bastiani and N.J. Shah and R. Goebel and A. Roebroeck",
year = "2012",
month = "9",
doi = "10.1016/j.neuroimage.2012.06.002",
language = "English",
volume = "62",
pages = "1732--1749",
journal = "Neuroimage",
issn = "1053-8119",
publisher = "Elsevier Science",
number = "3",

}

Human cortical connectome reconstruction from diffusion weighted MRI: The effect of tractography algorithm. / Bastiani, M.; Shah, N.J.; Goebel, R.; Roebroeck, A.

In: Neuroimage, Vol. 62, No. 3, 09.2012, p. 1732-1749.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Human cortical connectome reconstruction from diffusion weighted MRI: The effect of tractography algorithm

AU - Bastiani, M.

AU - Shah, N.J.

AU - Goebel, R.

AU - Roebroeck, A.

PY - 2012/9

Y1 - 2012/9

N2 - Reconstructing the macroscopic human cortical connectome by Diffusion Weighted Imaging (DWI) is a challenging research topic that has recently gained a lot of attention. In the present work, we investigate the effects of intra-voxel fiber direction modeling and tractography algorithm on derived structural network indices (e.g. density, small-worldness and global efficiency). The investigation is centered on three semi-independent distinctions within the large set of available diffusion models and tractography methods: i) single fiber direction versus multiple directions in the intra-voxel diffusion model, ii) deterministic versus probabilistic tractography and iii) local versus global measure-of-fit of the reconstructed fiber trajectories. The effect of algorithm and parameter choice has two components. First, there is the large effect of tractography algorithm and parameters on global network density, which is known to strongly affect graph indices. Second, and more importantly, there are remaining effects on graph indices which range in the tens of percent even when global density is controlled for. This is crucial for the sensitivity of any human structural network study and for the validity of study comparisons. We then investigate the effect in choices in tractography algorithm on sensitivity and specificity of the resulting connections with a connectome dissection quality control (QC) approach. In this approach, evaluation of Tract Specific Density Coefficients (TSDCs) measures sensitivity while careful inspection of tractography path results assesses specificity. We use this to discuss interactions in the combined effects of these methods and implications for future studies.

AB - Reconstructing the macroscopic human cortical connectome by Diffusion Weighted Imaging (DWI) is a challenging research topic that has recently gained a lot of attention. In the present work, we investigate the effects of intra-voxel fiber direction modeling and tractography algorithm on derived structural network indices (e.g. density, small-worldness and global efficiency). The investigation is centered on three semi-independent distinctions within the large set of available diffusion models and tractography methods: i) single fiber direction versus multiple directions in the intra-voxel diffusion model, ii) deterministic versus probabilistic tractography and iii) local versus global measure-of-fit of the reconstructed fiber trajectories. The effect of algorithm and parameter choice has two components. First, there is the large effect of tractography algorithm and parameters on global network density, which is known to strongly affect graph indices. Second, and more importantly, there are remaining effects on graph indices which range in the tens of percent even when global density is controlled for. This is crucial for the sensitivity of any human structural network study and for the validity of study comparisons. We then investigate the effect in choices in tractography algorithm on sensitivity and specificity of the resulting connections with a connectome dissection quality control (QC) approach. In this approach, evaluation of Tract Specific Density Coefficients (TSDCs) measures sensitivity while careful inspection of tractography path results assesses specificity. We use this to discuss interactions in the combined effects of these methods and implications for future studies.

KW - Diffusion weighted magnetic resonance

KW - imaging

KW - Tractography

KW - Human connectome

KW - Structural network analysis

KW - Quality control

KW - Tract specific density coefficient

KW - PROBABILISTIC FIBER TRACKING

KW - LIVING HUMAN BRAIN

KW - TENSOR MRI

KW - SPHERICAL DECONVOLUTION

KW - CROSSING FIBERS

KW - RESOLUTION

KW - MATTER

KW - CONNECTIVITY

KW - NETWORKS

KW - ARCHITECTURE

U2 - 10.1016/j.neuroimage.2012.06.002

DO - 10.1016/j.neuroimage.2012.06.002

M3 - Article

VL - 62

SP - 1732

EP - 1749

JO - Neuroimage

JF - Neuroimage

SN - 1053-8119

IS - 3

ER -