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Impact of fMRI-guided advanced DTI fiber tracking techniques on their clinical applications in patients with brain tumors


Kleiser, R; Staempfli, P; Valavanis, A; Boesiger, P; Kollias, S S (2010). Impact of fMRI-guided advanced DTI fiber tracking techniques on their clinical applications in patients with brain tumors. Neuroradiology, 52(1):37-46.

Abstract

Introduction: White matter tractography based on diffusion
tensor imaging has become a well-accepted non-invasive
tool for exploring the white matter architecture of the
human brain in vivo. There exist two main key obstacles
for reconstructing white matter fibers: firstly, the implementation and application of a suitable tracking algorithm, which is capable of reconstructing anatomically complex fascicular pathways correctly, as, e.g., areas of fiber crossing or branching; secondly, the definition of an
appropriate tracking seed area for starting the reconstruction process. Large intersubject, anatomical variations make it difficult to define tracking seed areas based on reliable anatomical landmarks. An accurate definition of seed regions for the reconstruction of a specific neuronal pathway becomes even more challenging in patients suffering from space occupying pathological processes as, e.g., tumors due to the displacement of the tissue and the distortion of anatomical landmarks around the lesion.
Methods: To resolve the first problem, an advanced tracking
algorithm, called advanced fast marching, was applied in
this study. The second challenge was overcome by
combining functional magnetic resonance imaging (fMRI)
and diffusion tensor imaging (DTI) in order to perform
fMRI-guided accurate definition of appropriate seed areas
for the DTI fiber tracking. In addition, the performance of
the tasks was controlled by a MR-compatible power device.
Results Application of this combined approach to eight
healthy volunteers and exemplary to three tumor patients
showed that it is feasible to accurately reconstruct relevant fiber tracts belonging to a specific functional system.
Conclusion: fMRI-guided advanced DTI fiber tracking has
the potential to provide accurate anatomical and functional
information for a more informed therapeutic decision
making.

Introduction: White matter tractography based on diffusion
tensor imaging has become a well-accepted non-invasive
tool for exploring the white matter architecture of the
human brain in vivo. There exist two main key obstacles
for reconstructing white matter fibers: firstly, the implementation and application of a suitable tracking algorithm, which is capable of reconstructing anatomically complex fascicular pathways correctly, as, e.g., areas of fiber crossing or branching; secondly, the definition of an
appropriate tracking seed area for starting the reconstruction process. Large intersubject, anatomical variations make it difficult to define tracking seed areas based on reliable anatomical landmarks. An accurate definition of seed regions for the reconstruction of a specific neuronal pathway becomes even more challenging in patients suffering from space occupying pathological processes as, e.g., tumors due to the displacement of the tissue and the distortion of anatomical landmarks around the lesion.
Methods: To resolve the first problem, an advanced tracking
algorithm, called advanced fast marching, was applied in
this study. The second challenge was overcome by
combining functional magnetic resonance imaging (fMRI)
and diffusion tensor imaging (DTI) in order to perform
fMRI-guided accurate definition of appropriate seed areas
for the DTI fiber tracking. In addition, the performance of
the tasks was controlled by a MR-compatible power device.
Results Application of this combined approach to eight
healthy volunteers and exemplary to three tumor patients
showed that it is feasible to accurately reconstruct relevant fiber tracts belonging to a specific functional system.
Conclusion: fMRI-guided advanced DTI fiber tracking has
the potential to provide accurate anatomical and functional
information for a more informed therapeutic decision
making.

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50 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Biomedical Engineering
04 Faculty of Medicine > University Hospital Zurich > Clinic for Neuroradiology
Dewey Decimal Classification:170 Ethics
610 Medicine & health
Language:English
Date:2010
Deposited On:29 Sep 2009 13:16
Last Modified:05 Apr 2016 13:21
Publisher:Springer
ISSN:0028-3940
Additional Information:The original publication is available at www.springerlink.com
Publisher DOI:10.1007/s00234-009-0539-2
PubMed ID:19479248
Permanent URL: http://doi.org/10.5167/uzh-20818

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