Abstract
The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.
Highlights
The analysis of micro structural white matter properties has become increasingly important, especially in multiple sclerosis research (Deppe et al, 2007, 2014, 2016)
There are several techniques such as diffusion-weighted magnet resonance imaging (DWI) that are sensitive to white matter alterations that cannot be assessed by conventional MRI
The images in the second column show the actual result of the developed white matter parcellation method
Summary
The analysis of micro structural white matter properties has become increasingly important, especially in multiple sclerosis research (Deppe et al, 2007, 2014, 2016). Korbinian Brodmann introduced the first parcellation method for the cortex in 1909 by classifying cortex areas by their cytoarchitecture (Brodmann, 1909). Through the rise of structural MRI in brain imaging, in vivo cortex parcellation became possible (Rademacher et al, 1992) by classifying the cortex on the basis of cortical gyri and sulci, providing a way to associate cortex alterations to brain functions. Further cortex parcellations were created which seek to provide a higher resolution through defining more cortex labels (Desikan et al, 2006; Destrieux et al, 2010), or to classify the cortex from functional networks derived from functional MRI (Craddock et al, 2012; Blumensath et al, 2013; Shen et al, 2013; Moreno-Dominguez et al, 2014; Thirion et al, 2014; Parisot et al, 2016)
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