scholarly journals Association between in-scanner head motion with cerebral white matter microstructure: a multiband diffusion-weighted MRI study

PeerJ ◽  
2014 ◽  
Vol 2 ◽  
pp. e366 ◽  
Author(s):  
Xiang-zhen Kong
2014 ◽  
Author(s):  
Xiang-zhen Kong

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 technique, 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.


2014 ◽  
Author(s):  
Xiang-zhen Kong

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 technique, 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.


2014 ◽  
Author(s):  
Xiang-zhen Kong

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 technique, 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.


2014 ◽  
Author(s):  
Xiang-zhen Kong

Diffusion-weighted MRI (DW-MRI) has emerged as a promising neuroimaging technique used to depict the biological microstructural properties of the human brain white matter. However, like any other MRI technique, DW-MRI remains subject to head motion during scanning. The association between motion and diffusion metrics is rarely understood. Previous studies have indicated that there are some regions showing significant relationship with diffusion metrics from traditional DW-MRI data with relative few gradient directions (e.g., 30 directions). As imaging techniques improves, additional gradient directions can be acquired in the same scan duration without a significant loss in spatial resolution. The current study examined the association between motion and diffusion metrics with the standard pipeline, tract-based spatial statistics (TBSS), with a multiband diffusion data (i.e., 137 directions). The diffusion metrics used in this study not only the included the commonly used metrics (i.e., FA and MD) in DW-MRI studies, but also a newly proposed inter-voxel metric, local diffusion homogeneity (LDH). The positive association was observed with MD, while the negative association with LDH. No significant association between motion and FA was observed. These results indicate that there is a similar link between motion and diffusion metrics in the multiband diffusion data. Finally, the motion-diffusion association is discussed.


2021 ◽  
Vol 89 (9) ◽  
pp. S184-S185
Author(s):  
Katherine Lawrence ◽  
Leila Nabulsi ◽  
Vigneshwaran Santhalingam ◽  
Zvart Abaryan ◽  
Julio Villalon-Reina ◽  
...  

Pain ◽  
2012 ◽  
Vol 153 (3) ◽  
pp. 651-656 ◽  
Author(s):  
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Zsigmond Tamás Kincses ◽  
Árpád Párdutz ◽  
János Tajti ◽  
Délia Szok ◽  
...  

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