Abstract
Diffusion-weighted MRI (DW-MRI), the only non-invasive technique for probing human brain white matter structures in vivo, has been widely used in both fundamental studies and clinical applications. Many studies have utilized diffusion tensor imaging (DTI) and tractography approaches to explore the topological properties of human brain anatomical networks by using the single tensor model, the basic model to quantify DTI indices and tractography. However, the conventional DTI technique does not take into account contamination by the cerebrospinal fluid (CSF), which has been known to affect the estimated DTI measures and tractography in the single tensor model. Previous studies have shown that the Fluid-Attenuated Inversion Recovery (FLAIR) technique can suppress the contribution of the CSF to the DW-MRI signal. We acquired DTI datasets from twenty-two subjects using both FLAIR-DTI and conventional DTI (non-FLAIR-DTI) techniques, constructed brain anatomical networks using deterministic tractography, and compared the topological properties of the anatomical networks derived from the two types of DTI techniques. Although the brain anatomical networks derived from both types of DTI datasets showed small-world properties, we found that the brain anatomical networks derived from the FLAIR-DTI showed significantly increased global and local network efficiency compared with those derived from the conventional DTI. The increases in the network regional topological properties derived from the FLAIR-DTI technique were observed in CSF-filled regions, including the postcentral gyrus, periventricular regions, inferior frontal and temporal gyri, and regions in the visual cortex. Because brain anatomical networks derived from conventional DTI datasets with tractography have been widely used in many studies, our findings may have important implications for studying human brain anatomical networks derived from DW-MRI data and tractography.
Highlights
Diffusion-weighted magnetic resonance imaging (DW-MRI) is the only available tool for non-invasively probing human brain tissue microstructure and the microanatomical organization of human brain white matter in vivo
We calculated the values of l and c for the human brain anatomical networks derived from the conventional diffusion tensor imaging (DTI) and FluidAttenuated Inversion Recovery (FLAIR)-DTI datasets
We compared the topological properties of human brain anatomical networks constructed using graph theory and utilizing datasets collected by conventional DTI and FLAIR-DTI techniques
Summary
Diffusion-weighted magnetic resonance imaging (DW-MRI) is the only available tool for non-invasively probing human brain tissue microstructure and the microanatomical organization of human brain white matter in vivo. Recent advances in diffusion tensor imaging (DTI) techniques and white matter tractography have made it possible to visualize the fiber tracts comprised of coherently oriented axons and to map the anatomical connectivity patterns of healthy and diseased human brains [1,2,3,4]. A potential problem which affects the accuracy of tractography and the estimated DTI metrics derived from the single tensor model, but which is often ignored, is contamination by cerebrospinal fluid (CSF) [19,20,21,22,23]. If a voxel contain CSF and brain tissue, the accuracy of its diffusion tensor measurement and the diffusion parameter of the brain tissue estimated using the single tensor model may be significantly influenced [17,18,19,24]. Previous studies showed that CSF contamination can significantly influence diffusion measurements in ways such as overestimating the apparent diffusion coefficient (ADC) by about 15–30% [21] and underestimating the diffusion anisotropy [17,25,26,27]
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