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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
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Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review
Fan Zhang1, Alessandro Daducci2, Yong He3
1Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Neuroimage
|January 3, 2022
Summary
Diffusion magnetic resonance imaging (dMRI) tractography reconstructs brain white matter connections. Quantitative analysis of these connections aids understanding of brain health and disease, though no single best method exists.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- Brain Connectomics
Background:
- Diffusion magnetic resonance imaging (dMRI) tractography reconstructs in vivo brain white matter connections.
- It is crucial for quantitative mapping of structural connectivity and tissue microstructure.
- dMRI tractography has been a cornerstone of neuroimaging research for two decades.
Purpose of the Study:
- To provide a high-level overview of quantitative tractography for analyzing brain structural connectivity.
- To review methodologies for tractography correction, segmentation, and quantification.
- To survey applications of quantitative tractography in health and disease.
Main Methods:
- Review of common processing steps: tractography correction, segmentation, and quantification.
- Discussion of methodological choices, popularity, pros, and cons for each step.
- Synthesis of studies applying quantitative tractography in various neurological and developmental contexts.
Main Results:
- Tractography enables quantitative analysis of brain structural connectivity.
- Two main analysis types: tract-specific and connectome-based.
- Applications span neurodevelopment, aging, neurological/mental disorders, and neurosurgery.
Conclusions:
- Significant advancements in dMRI tractography methodologies and applications exist.
- There is no established consensus on the optimal quantitative analysis methodology.
- Researchers must exercise caution when interpreting results in research and clinical settings.

