Software Packages for DTI/DWI QC and Analysis
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Software Packages for DTI/DWI QC and Analysis UNC Styner Group & Utah Gerig Group April 2014
Transcript of Software Packages for DTI/DWI QC and Analysis
Software Packages for DTI/DWI QC and Analysis
UNC Styner Group &
Utah Gerig Group
April 2014
Disclaimer
I don’t talk about MINC software
But
I discuss open-source/open-platform software freely available to the scientific community
& linked to MINC via Vladimirs itk file format conversion tools (nifty, nrrd, meta, gipl, etc.)
Alexander Leemans ([email protected])
http://www.samsi.info/workshop/summer-2013-neuroimaging-data-analysis-june-4-14-2013
Alexander Leemans ([email protected])
Hi Alex, I have been collecting “advanced DTI data”. Can you help me with the analysis?*
* Read: “Can you do the analysis for me?”
Alexander Leemans ([email protected])
Alexander Leemans ([email protected])
Alexander Leemans ([email protected]) Tournier J.-D. et al, Magn Reson Med (2011)
Our Approach • Assume that there is always a QC problem: Hardware, scanning
sequence, coils, export, protocol violation, table vibrations, subject motion, FOV errors, DICOM conversion, problems with analysis software.
• To develop and disseminate (open-source, open-platform) advanced QC software for quantitative analysis of image quality and for image correction.
• To publish papers associated with QC tools and methods → to raise awareness and inform.
• To develop guidelines for researchers and clinical users on how best to correct data for artifacts.
• Rules to become standard: No journal article on DWI use should be accepted unless researchers prove that there is rigorous QC testing and quantitative evidence that reported results are not a confounding factor of artifacts.
National Alliance for Medical Image Computing http://na-mic.org Slide 9
Diffusion Artifacts
Diffusion images are sensitive to a number of artifacts
• Motion
• Eddy-current distortions
• Noise/SNR issues
• Vibrational artifacts
• Venetian blind artifacts
• “unknown”…
Bad DWI’s are removed/corrected
Need tools that go beyond eyeballing
ACE-IBIS infant study, >1200 DWI (25 directions, >50 slices)
• Oguz, M. Farzinfar, J. Matsui, F. Budin, Z. Liu, G. Gerig, H.J. Johnson, M.A. Styner. “DTIPrep: Quality Control of
Diffusion-Weighted Images,” In Frontiers in Neuroinformatics, Vol. 8, No. 4, 2014. DOI: 10.3389/fninf.2014.00004
• PDF: http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00004/full
• Instruction manuals, Slicer and NITRC downloads: http://www.na-mic.org/Wiki/index.php/SPIE_2013_DTI_Workshop
M. Styner et al., UNC Chapel Hill & Gerig et al., Utah group.
National Alliance for Medical Image Computing http://na-mic.org Slide 15
QC Result
• Loads QC’ed DWI
when finished
• Detailed reporting
• Directions after
motion correction
• Reasons for
exclusion
Assume there is always Motion
Average and standard deviation of the percentage of motion-corrupted gradient directions as a function of thresholding on the estimated rotation angle in degrees (left) and the estimated translation magnitude in mm (right) for three human phantoms scanned twice at four clinical sites. Boxplots: Overall statistics of estimated motion parameters.
24 multi-site DWI scans of human phantom
Alexander Leemans ([email protected])
“Subject motion”
Leemans A. & Jones D.K., Magn Reson Med (2009)
Alexander Leemans ([email protected])
“Corrected for subject motion”
Leemans A. & Jones D.K., Magn Reson Med (2009)
Motion correction by DTIprep
Motion correction by DTIprep
Testing the Testing: S. Elhabian and G. Gerig, Utah
QA analysis of ODF construction (anisotropy of the dominant fiber), dipy analysis package.
Stripes seem bug in dipy analysis SW. QA analysis of ODF construction (reprogrammed). QC needs COMMUNITY EFFORT!
System’s Approach: Elhabian et al., submitted
3D Slicer (NA-MIC, R. Kikinis)
DWI software: Instruction manuals, Slicer and NITRC downloads:
http://www.na-mic.org/Wiki/index.php/SPIE_2013_DTI_Workshop
Details: Frontiers paper: DOI: 10.3389/fninf.2013.00051
www.slicer.org
UNC-Utah DTI Fiber Analysis • Analysis of DTI properties along the fiber
• Many years of methods & tool development
• Allows for localized analysis with high sensitivity
A.R. Verde, F. Budin, , G. Gerig, M. Styner. “UNC-Utah NA-MIC framework for DTI fiber tract analysis,” In Frontiers in Neuroinformatics, (7)51, Jan, 2014. DOI: 10.3389/fninf.2013.00051
I: DTI atlas building Combined v06-v12-v24 DTI atlas, Clement Vachet, Utah) (September: 978 data points, ACE-IBIS project)
Concept: S. Joshi, B. Davis, M Jomier, G. Gerig. “Unbiased Diffeomorphic Atlas Construction for Computational Anatomy,” In Neuroimage, Vol. 23 Suppl. 1, pp. S151--S160. 2004.
II: Tractography in Atlas Space: Use your favorite algorithm
Example Utah DS study: Tractography in atlas space of 17 healthy controls, language related tracts (unpublished)
• DSIstudio • 3D Slicer • DTIstudio • MINC tools • UNCTrack • dpy toolbox • Etc.
III: Tract Parametrization
Corouge et al. Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis. Medical Image Analysis 2006.
IIIb Tract Modeling: FiberViewer Light
FIberViewerLight: http://www.nitrc.org/projects/fvlight/
IV: Mapping tract back to original space
V: Statistics: Functional Data Analysis (FDA) on Fiber Bundles
Hongbin Gu: Longitudinal modeling with covariates
Hongtu Zhu: FMVCM
multiple diffusion properties along major white matter fiber bundles and their association with a set of covariates
V: Example: Tract diffusion development versus age
X. Geng, S. Gouttard, A. Sharma, H. Gu, M. Styner, W. Lin, G. Gerig, J.H. Gilmore. “Quantitative Tract-Based White Matter Development from Birth to Age Two Years,” In NeuroImage, pp. 1-44. March, 2012. DOI: 10.1016/j.neuroimage.2012.03.057
History:
• 2000/2001: SNAP Prototype: Student semester projects UNC Chapel Hill, G. Gerig
• 2003: NLM funding to port to ITK (Paul Yushkevich, U-Penn)
• 2004: itk-SNAP released, Linux, Windows and MacOS
• 2007: NIBIB R03 (Yushkevich), itk-SNAP 2.x
• 2012-14: NIBIB R01 (Yushkevich/Gerig) Multimodal itk-SNAP
Functionality:
• 3D level-set segmentation with step-by-step user-guidance for complex pipeline, open-source, open-platform
• Full 3D interactive editing in 2D and 3D.
• http://www.itksnap.org
MRIWatcher
MRIWatcher: ITK SW for quick
viewing of large #3D datasets,
with coupled zoom/scroll,
overlays, info: Quick QC,
reviewing, comparison.
MriWatcher: http://www.nitrc.org/projects/mriwatcher/
ABC: Atlas Based Classification Fully automatic, atlas-moderated segmentation pipeline • Stand-alone (http://www.nitrc.org/projects/abc) software system,
former EMS, so far applied to over 5000 brain MRI • Slicer plugin module (Utah: Prastawa, Gerig) • Flexible use of probabilistic atlases (infants, adults, monkeys) • Deformable registration of probabilistic atlas (fluid multimod.) • Multi-modal co-registration, arbitrary #channels • Includes pre-filtering, brain stripping, and bias-correction • Output: Posterior probabilities, binary label maps
Other tools: (collab. with M. Styner, UNC)
All tools come with comprehensive tutorials
http://www.ia.unc.edu/dev/download/index.htm
