DCP: A pipeline toolbox for diffusion connectome

Hum Brain Mapp. 2024 Feb 15;45(3):e26626. doi: 10.1002/hbm.26626.

Abstract

The brain structural network derived from diffusion magnetic resonance imaging (dMRI) reflects the white matter connections between brain regions, which can quantitatively describe the anatomical connection pattern of the entire brain. The development of structural brain connectome leads to the emergence of a large number of dMRI processing packages and network analysis toolboxes. However, the fully automated network analysis based on dMRI data remains challenging. In this study, we developed a cross-platform MATLAB toolbox named "Diffusion Connectome Pipeline" (DCP) for automatically constructing brain structural networks and calculating topological attributes of the networks. The toolbox integrates a few developed packages, including FSL, Diffusion Toolkit, SPM, Camino, MRtrix3, and MRIcron. It can process raw dMRI data collected from any number of participants, and it is also compatible with preprocessed files from public datasets such as HCP and UK Biobank. Moreover, a friendly graphical user interface allows users to configure their processing pipeline without any programming. To prove the capacity and validity of the DCP, two tests were conducted with using DCP. The results showed that DCP can reproduce the findings in our previous studies. However, there are some limitations of DCP, such as relying on MATLAB and being unable to fixel-based metrics weighted network. Despite these limitations, overall, the DCP software provides a standardized, fully automated computational workflow for white matter network construction and analysis, which is beneficial for advancing future human brain connectomics application research.

Keywords: DCP; dMRI; diffusion connectome; diffusion tensor imaging; graph theory; structural connectivity; structure network; white matter.

MeSH terms

  • Brain / diagnostic imaging
  • Connectome* / methods
  • Diffusion Magnetic Resonance Imaging / methods
  • Humans
  • Image Processing, Computer-Assisted / methods
  • White Matter* / diagnostic imaging