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UNC-Utah NA-MIC DTI framework: Atlas Based Fiber Tract Analysis with Application to a Study of Nicotine Smoking Addiction

Institution:
1Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
2Psychology, University of North Carolina, Chapel Hill, NC, USA.
3Computer Science, University of North Carolina, Chapel Hill, NC, USA.
4Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
5Kitware Inc, Clifton Park, NY, USA.
6Biostatistics, University of North Carolina, Chapel Hill, NC, USA.
7University of Iowa, Iowa City, IO, USA.
Publication Date:
Mar-2013
Volume Number:
8669
Pages:
86692D-8.
Citation:
Proc SPIE. 2013 Mar 13;8669.
PubMed ID:
24386543
PMCID:
PMC3877245
Keywords:
Diffusion Tensor Imaging, Tractography, Diffusion Imaging Quality Control, DTI Atlas Building, Smoking Addiction
Appears in Collections:
NA-MIC, SLICER
Sponsors:
NSF BCS-08-26844
U54 EB005149/EB/NIBIB NIH HHS/United States
P50 MH064065/MH/NIMH NIH HHS/United States
P30 HD003110/HD/NICHD NIH HHS/United States
R01 MH070890/MH/NIMH NIH HHS/United States
P50 MH078105/MH/NIMH NIH HHS/United States
UL1 RR025747/RR/NCRR NIH HHS/United States
P01 CA142538/CA/NCI NIH HHS/United States
R01 MH086633/MH/NIMH NIH HHS/United States
R21 AG033387/AG/NIA NIH HHS/United States
R01 HD053000/HD/NICHD NIH HHS/United States
R01 MH091645/MH/NIMH NIH HHS/United States
T32 NS007431/NS/NINDS NIH HHS/United States
R01 AI067518/AI/NIAID NIH HHS/United States
Generated Citation:
Verde A.R., Berger J-B., Gupta A., Farzinfar M., Kaiser A., Chanon V.W., Boettiger C., Johnson H., Matsui J., Sharma A., Goodlett C., Shi Y., Zhu H., Gerig G., Gouttard S., Vachet C., Styner M. UNC-Utah NA-MIC DTI framework: Atlas Based Fiber Tract Analysis with Application to a Study of Nicotine Smoking Addiction. Proc SPIE. 2013 Mar 13;8669. PMID: 24386543. PMCID: PMC3877245.
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Purpose: The UNC-Utah NA-MIC DTI framework represents a coherent, open source, atlas fiber tract based DTI analysis framework that addresses the lack of a standardized fiber tract based DTI analysis workflow in the field. Most steps utilize graphical user interfaces (GUI) to simplify interaction and provide an extensive DTI analysis framework for non-technical researchers/investigators. Data: We illustrate the use of our framework on a 54 directional DWI neuroimaging study contrasting 15 Smokers and 14 Controls. Method(s): At the heart of the framework is a set of tools anchored around the multi-purpose image analysis platform 3D Slicer. Several workflow steps are handled via external modules called from Slicer in order to provide an integrated approach. Our workflow starts with conversion from DICOM, followed by thorough automatic and interactive quality control (QC), which is a must for a good DTI study. Our framework is centered around a DTI atlas that is either provided as a template or computed directly as an unbiased average atlas from the study data via deformable atlas building. Fiber tracts are defined via interactive tractography and clustering on that atlas. DTI fiber profiles are extracted automatically using the atlas mapping information. These tract parameter profiles are then analyzed using our statistics toolbox (FADTTS). The statistical results are then mapped back on to the fiber bundles and visualized with 3D Slicer. Results: This framework provides a coherent set of tools for DTI quality control and analysis. Conclusions: This framework will provide the field with a uniform process for DTI quality control and analysis.

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