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Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

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 su...

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Autores principales: Schiffler, Patrick, Tenberge, Jan-Gerd, Wiendl, Heinz, Meuth, Sven G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498510/
https://www.ncbi.nlm.nih.gov/pubmed/28729829
http://dx.doi.org/10.3389/fnhum.2017.00352
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author Schiffler, Patrick
Tenberge, Jan-Gerd
Wiendl, Heinz
Meuth, Sven G.
author_facet Schiffler, Patrick
Tenberge, Jan-Gerd
Wiendl, Heinz
Meuth, Sven G.
author_sort Schiffler, Patrick
collection PubMed
description 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.
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spelling pubmed-54985102017-07-20 Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects Schiffler, Patrick Tenberge, Jan-Gerd Wiendl, Heinz Meuth, Sven G. Front Hum Neurosci Neuroscience 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. Frontiers Media S.A. 2017-07-06 /pmc/articles/PMC5498510/ /pubmed/28729829 http://dx.doi.org/10.3389/fnhum.2017.00352 Text en Copyright © 2017 Schiffler, Tenberge, Wiendl and Meuth. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Schiffler, Patrick
Tenberge, Jan-Gerd
Wiendl, Heinz
Meuth, Sven G.
Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title_full Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title_fullStr Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title_full_unstemmed Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title_short Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
title_sort cortex parcellation associated whole white matter parcellation in individual subjects
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498510/
https://www.ncbi.nlm.nih.gov/pubmed/28729829
http://dx.doi.org/10.3389/fnhum.2017.00352
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