Abstract
Abstract Introduction: The search for human brain templates has been progressing in the past decades and in order to understand disease patterns a need for a standard diffusion tensor imaging (DTI) dataset was raised. For this purposes, some DTI templates were developed which assist group analysis studies. In this study, complementary information to the most commonly used DTI template is proposed in order to offer a patient-specific statistical analysis on diffusion-weighted data. Methods 131 normal subjects were used to reconstruct a population-averaged template. After image pre processing, reconstruction and diagonalization, the eigenvalues and eigenvectors were used to reconstruct the quantitative DTI maps, namely fractional anisotropy (FA), mean diffusivity (MD), relative anisotropy (RA), and radial diffusivity (RD). The mean absolute error (MAE) was calculated using a voxel-wise procedure, which informs the global error regarding the mean intensity value for each quantitative map. Results the MAE values presented a low MAE estimate (max(MAE) = 0.112), showing a reasonable error measure between our DTI-USP-131 template and the classical DTI-JHU-81 approach, which also shows a statistical equivalence (p<0.05) with the classical DTI template. Hence, the complementary standard deviation (SD) maps for each quantitative DTI map can be added to the classical DTI-JHU-81 template. Conclusion In this study, variability DTI maps (SD maps) were reconstructed providing the possibility of a voxel-wise statistical analysis in patient-specific approach. Finally, the brain template (DTI-USP-131) described here was made available for research purposes on the web site (http://dx.doi.org/10.17632/br7bhs4h7m.1), being valuable to research and clinical applications.
Highlights
The search for human brain templates has been progressing in the past decades and in order to understand disease patterns a need for a standard diffusion tensor imaging (DTI) dataset was raised
We introduce a complementary DTI template for the widely used DTI-JHU-81 brain template (Mori et al, 2008), which aims to add the variability information on the mean DTI maps already provided in the classical DTI template offered by Mori et al (2008)
The fractional anisotropy (FA) was chosen only for simplicity and the same procedure could be visualized on the other quantitative maps (i.e. mean diffusivity (MD), relative anisotropy (RA), and radial diffusivity (RD))
Summary
The search for human brain templates has been progressing in the past decades and in order to understand disease patterns a need for a standard diffusion tensor imaging (DTI) dataset was raised. For this purposes, some DTI templates were developed which assist group analysis studies. The most widely used atlases was one by Talairach and Tournoux (Talairach, 1988), being based on histology data from a single subject Another example of well-known brain template is the cytoarchitectural map of the cortex by Brodmann’s map (Brodmann, 2005), which has been widely used for image registering, identifying, and reporting human cortical locations in a common coordinate system (Strotzer, 2009; Thottakara et al, 2006; Zilles and Amunts, 2010).
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