Abstract
Diffusion MRI tractography has been used to map the axonal structure of the human brain, but its ability to detect neuronal injury is yet to be explored. Here we report differential tractography, a new type of tractography that utilizes repeat MRI scans and a novel tracking strategy to map the exact segment of fiber pathways with a neuronal injury. We examined differential tractography on multiple sclerosis, Huntington’s disease, amyotrophic lateral sclerosis, and epileptic patients. The results showed that the affected pathways shown by differential tractography matched well with the unique clinical symptoms of the patients, and the false discovery rate of the findings could be estimated using a sham setting to provide a reliability measurement. This novel approach enables a quantitative and objective method to monitor neuronal injury in individuals, allowing for diagnostic and prognostic evaluation of brain diseases.
Highlights
Magnetic resonance imaging (MRI) is a commonly used neuroimaging technique for revealing a structural change in patients with neurological disorders
The rationale behind this length threshold is that the local random error does not propagate along fiber pathways, whereas true findings due to neuronal injury will form a continuous decrease of anisotropy along the fiber bundles
We report a novel tractography method to reveal fiber pathways affected by a neuronal injury
Summary
Magnetic resonance imaging (MRI) is a commonly used neuroimaging technique for revealing a structural change in patients with neurological disorders. Studies have used structural MRI to reveal gray matter atrophy in patients with multiple sclerosis (Rovira et al, 2015; Wattjes et al, 2015) and atrophy in the caudate in patients with Huntington disease (Tabrizi et al, 2009; Tabrizi et al, 2012). Animal studies have used diffusion tensor imaging (DTI)(Basser et al, 1994) to detect acute demyelination or axonal loss (Song et al, 2002; Song et al., 2005). The decrease of anisotropic diffusion has been shown to be correlated with axonal loss (Budde et al, 2009; Huisman et al, 2004; Werring et al, 1999; Werring et al, 2000). Anisotropy remains a voxel-based measurement, which is prone to local variations such as partial volume effect (Henf et al., 2018; Wang et al, 2011) or signal noise, thereby limiting its clinical applications (Melonakos et al, 2011)
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