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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Integrated diffusion image operator (iDIO): A pipeline for automated configuration and processing of diffusion MRI

Chih-Chin Heather Hsu1,2, Shin Tai Chong1, Yi-Chia Kung1,3

  • 1Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan.

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|February 22, 2023
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Summary

The integrated diffusion image operator (iDIO) simplifies diffusion MRI (dMRI) analysis with a semi-automated pipeline. It offers adaptive preprocessing and quality control, reducing barriers for nonexpert users in dMRI research.

Keywords:
connectomediffusion MRIimage preprocessingpipeline toolsemi-automated processing

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Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Data Science

Background:

  • Diffusion MRI (dMRI) preprocessing involves complex steps like motion and distortion correction.
  • Varied acquisition schemes necessitate custom configurations, increasing the technical barrier for dMRI analysis.
  • Inconsistent processing hinders comparability across dMRI studies.

Purpose of the Study:

  • To introduce a semi-automated pipeline tool, the integrated diffusion image operator (iDIO), for transparent and adaptive dMRI data processing.
  • To lower the technical threshold for dMRI analysis, especially for nonexpert researchers and clinicians.
  • To ensure comparability between studies by standardizing and simplifying dMRI preprocessing.

Main Methods:

  • Developed iDIO, a semi-automated pipeline integrating advanced dMRI software.
  • Implemented adaptive configuration based on image headers for suggested processing steps.
  • Included post-processing options: diffusion tensor metrics and tractography-based connectomes reconstruction.
  • Integrated a quality control report, execution logs, and accessible intermediate images for transparency.

Main Results:

  • iDIO provides a one-click solution for dMRI data analysis.
  • The pipeline adapts preprocessing steps based on input data characteristics.
  • Users can perform advanced analyses like diffusion tensor imaging and connectomics.
  • A comprehensive quality control report aids in data quality assessment.

Conclusions:

  • iDIO significantly reduces barriers for clinical and nonspecialist users in adopting state-of-the-art dMRI processing.
  • The tool enhances transparency and adaptability in dMRI data analysis.
  • iDIO promotes standardized and comparable dMRI research outcomes.