Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.

Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative de...

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Autores principales:	Miriam H A Bauer, Daniela Kuhnt, Sebastiano Barbieri, Jan Klein, Andreas Becker, Bernd Freisleben, Horst K Hahn, Christopher Nimsky
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9aaf843959284073934e6a1679588df3
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spelling	oai:doaj.org-article:9aaf843959284073934e6a1679588df32021-11-18T07:46:47ZReconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.1932-620310.1371/journal.pone.0063082https://doaj.org/article/9aaf843959284073934e6a1679588df32013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23671656/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative deficits while maximizing the tumor resection volume. Since routinely used deterministic streamline tractography approaches often underestimate the spatial extent of white matter tracts, a novel approach to improve fiber segmentation is presented here, considering clinical time constraints. Therefore, fiber tracking visualization is enhanced with statistical information from multiple tracking applications to determine uncertainty in reconstruction based on clinical DTI data. After initial deterministic fiber tracking and centerline calculation, new seed regions are generated along the result's midline. Tracking is applied to all new seed regions afterwards, varying in number and applied offset. The number of fibers passing each voxel is computed to model different levels of fiber bundle membership. Experimental results using an artificial data set of an anatomical software phantom are presented, using the Dice Similarity Coefficient (DSC) as a measure of segmentation quality. Different parameter combinations were classified to be superior to others providing significantly improved results with DSCs of 81.02%±4.12%, 81.32%±4.22% and 80.99%±3.81% for different levels of added noise in comparison to the deterministic fiber tracking procedure using the two-ROI approach with average DSCs of 65.08%±5.31%, 64.73%±6.02% and 65.91%±6.42%. Whole brain tractography based on the seed volume generated by the calculated seeds delivers average DSCs of 67.12%±0.86%, 75.10%±0.28% and 72.91%±0.15%, original whole brain tractography delivers DSCs of 67.16%, 75.03% and 75.54%, using initial ROIs as combined include regions, which is clearly improved by the repeated fiber tractography method.Miriam H A BauerDaniela KuhntSebastiano BarbieriJan KleinAndreas BeckerBernd FreislebenHorst K HahnChristopher NimskyPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 5, p e63082 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Miriam H A Bauer Daniela Kuhnt Sebastiano Barbieri Jan Klein Andreas Becker Bernd Freisleben Horst K Hahn Christopher Nimsky Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
description	Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative deficits while maximizing the tumor resection volume. Since routinely used deterministic streamline tractography approaches often underestimate the spatial extent of white matter tracts, a novel approach to improve fiber segmentation is presented here, considering clinical time constraints. Therefore, fiber tracking visualization is enhanced with statistical information from multiple tracking applications to determine uncertainty in reconstruction based on clinical DTI data. After initial deterministic fiber tracking and centerline calculation, new seed regions are generated along the result's midline. Tracking is applied to all new seed regions afterwards, varying in number and applied offset. The number of fibers passing each voxel is computed to model different levels of fiber bundle membership. Experimental results using an artificial data set of an anatomical software phantom are presented, using the Dice Similarity Coefficient (DSC) as a measure of segmentation quality. Different parameter combinations were classified to be superior to others providing significantly improved results with DSCs of 81.02%±4.12%, 81.32%±4.22% and 80.99%±3.81% for different levels of added noise in comparison to the deterministic fiber tracking procedure using the two-ROI approach with average DSCs of 65.08%±5.31%, 64.73%±6.02% and 65.91%±6.42%. Whole brain tractography based on the seed volume generated by the calculated seeds delivers average DSCs of 67.12%±0.86%, 75.10%±0.28% and 72.91%±0.15%, original whole brain tractography delivers DSCs of 67.16%, 75.03% and 75.54%, using initial ROIs as combined include regions, which is clearly improved by the repeated fiber tractography method.
format	article
author	Miriam H A Bauer Daniela Kuhnt Sebastiano Barbieri Jan Klein Andreas Becker Bernd Freisleben Horst K Hahn Christopher Nimsky
author_facet	Miriam H A Bauer Daniela Kuhnt Sebastiano Barbieri Jan Klein Andreas Becker Bernd Freisleben Horst K Hahn Christopher Nimsky
author_sort	Miriam H A Bauer
title	Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
title_short	Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
title_full	Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
title_fullStr	Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
title_full_unstemmed	Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
title_sort	reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/9aaf843959284073934e6a1679588df3
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Reconstruction of white matter tracts via repeated deterministic streamline tracking--initial experience.

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