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Updated: Apr 30, 2026
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Association between in-scanner head motion with cerebral white matter microstructure: a multiband diffusion-weighted
1State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China.
Abstract:
Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) has emerged as the most popular neuroimaging technique used to depict the biological microstructural properties of human brain white matter. However, like other MRI techniques, traditional DW-MRI data remains subject to head motion artifacts during scanning. For example, previous studies have indicated that, with traditional DW-MRI data, head motion artifacts significantly affect the evaluation of diffusion metrics. Actually, DW-MRI data scanned with higher sampling rate are important for accurately evaluating diffusion metrics because it allows for full-brain coverage through the acquisition of multiple slices simultaneously and more gradient directions. Here, we employed a publicly available multiband DW-MRI dataset to investigate the association between motion and diffusion metrics with the standard pipeline, tract-based spatial statistics (TBSS). The diffusion metrics used in this study included not only the commonly used metrics (i.e., FA and MD) in DW-MRI studies, but also newly proposed inter-voxel metric, local diffusion homogeneity (LDH). We found that the motion effects in FA and MD seems to be mitigated to some extent, but the effect on MD still exists. Furthermore, the effect in LDH is much more pronounced. These results indicate that researchers shall be cautious when conducting data analysis and interpretation. Finally, the motion-diffusion association is discussed.
Insights
Head motion artifacts in diffusion-weighted MRI (DW-MRI) impact diffusion metrics like FA, MD, and LDH. While some metrics show mitigation, LDH is particularly sensitive to motion, requiring careful analysis.
Area of Science:
- Neuroimaging
- Biomedical Engineering
- Radiology
Background:
- Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) is crucial for assessing white matter microstructure.
- Head motion during scanning introduces artifacts that can compromise diffusion metric accuracy.
- Higher sampling rates in DW-MRI are essential for precise diffusion metric evaluation.
Purpose of the Study:
- To investigate the association between head motion and diffusion metrics using a multiband DW-MRI dataset.
- To evaluate the impact of motion on standard diffusion metrics (FA, MD) and a novel metric (LDH).
- To assess motion effects within the standard tract-based spatial statistics (TBSS) pipeline.
Main Methods:
- Utilized a publicly available multiband DW-MRI dataset.
- Applied the tract-based spatial statistics (TBSS) pipeline for data analysis.
- Examined the impact of motion on fractional anisotropy (FA), mean diffusivity (MD), and local diffusion homogeneity (LDH).
Main Results:
- Motion effects on FA and MD were partially mitigated but remained significant for MD.
- Local diffusion homogeneity (LDH) exhibited a much more pronounced sensitivity to motion artifacts.
- The findings highlight the persistent influence of motion on diffusion metric interpretation.
Conclusions:
- Researchers must exercise caution during DW-MRI data analysis and interpretation due to motion artifacts.
- The study underscores the need for robust motion correction strategies in neuroimaging.
- Understanding motion-diffusion associations is critical for reliable white matter microstructure assessment.
