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Neuroimage. 2019 Jun 28;200:302-312. doi: 10.1016/j.neuroimage.2019.06.065. [Epub ahead of print]

Development of a transcallosal tractography template and its application to dementia.

Author information

1
Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA.
2
Department of Neurology and Fixel Center for Neurological Disease, College of Medicine, University of Florida, Gainesville, FL, USA.
3
Department of Neurology and McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
4
Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; Department of Neurology and Fixel Center for Neurological Disease, College of Medicine, University of Florida, Gainesville, FL, USA; Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA. Electronic address: vcourt@ufl.edu.

Abstract

Understanding the architecture of transcallosal connections would allow for more specific assessments of neurodegeneration across many fields of neuroscience, neurology, and psychiatry. To map these connections, we conducted probabilistic tractography in 100 Human Connectome Project subjects in 32 cortical areas using novel post-processing algorithms to create a spatially precise Trancallosal Tract Template (TCATT). We found robust transcallosal tracts in all 32 regions, and a topographical analysis in the corpus callosum largely agreed with well-established subdivisions of the corpus callosum. We then obtained diffusion MRI data from a cohort of patients with Alzheimer's disease (AD) and another with progressive supranuclear palsy (PSP) and used a two-compartment model to calculate free-water corrected fractional anisotropy (FAT) and free-water (FW) within the TCATT. These metrics were used to determine between-group differences and to determine which subset of tracts was best associated with cognitive function (Montreal Cognitive Assessment (MoCA)). In AD, we found robust between-group differences in FW (31/32 TCATT tracts) in the absence of between-group differences in FAT. FW in the inferior temporal gyrus TCATT tract was most associated with MoCA scores in AD. In PSP, there were widespread differences in both FAT and FW, and MoCA was predicted by FAT in the inferior frontal pars triangularis, preSMA, and medial frontal gyrus TCATT tracts as well as FW in the inferior frontal pars opercularis TCATT tract. The TCATT improves spatial localization of corpus callosum measurements to enhance the evaluation of treatment effects, as well as the monitoring of brain microstructure in relation to cognitive dysfunction and disease progression. Here, we have shown its direct relevance in capturing between-group differences and associating it with the MoCA in AD and PSP.

KEYWORDS:

Alzheimer's disease; Atlas; Corpus callosum; Free-water; Progressive supranuclear palsy; Template

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