Camino and DTI-TK: Advanced Diffusion MRI Pipeline for Traumatic Brain Injury
Camino and DTI-TK: Advanced Diffusion MRI Pipeline for Traumatic Brain InjuryGary Hui Zhang, PhD
Microstructure Imaging GroupCentre for Medical Image ComputingDepartment of Computer ScienceUniversity College London
26th of June, 2013
UCL Centre for Medical Image Computing
Microstructure imaging with diffusion MRIEstimatePredictSignalDiffusion MRI quantifywater mobility in tissue
Diffusion MRITissueCell size, shape, densityMembrane permeabilityOrientation distributionAxer, J. Neuro. Meth. 1999
HistologyTissue ModelingModel parameters arethe tissue microstructurefeature themselves!Virtual Histology
InferencePipeline for advanced diffusion MRI analysis
Imaging
Normalization
Localization
Inference
NormalizationPipeline for advanced diffusion MRI analysis
Imaging
LocalizationCamino: a platform for advanced diffusion MRI analysisImplements a rich hierarchy of analytic models for diffusion MRIProvides a robust framework for fitting diffusion MRI data to the modelsDelivers a sophisticated simulator for validating diffusion MRI modelsMonte Carlo Diffusion Simulator (Hall and Alexander, IEEE TMI 2009)
Available SubstratesGamma-Distributed RadiiCrossing CylindersMesh-based substrates
Permeable Cylinders
Diffusion SubstrateDisplacement PDFDiffusion MR SignalSimulation Pipeline
Rich hierarchy of analytic models of diffusion MRI (Panagiotaki et al, NeuroImage 2012)
StickCylinderGDRCylindersBallAstrosticksAstrocylindersSphereDotZeppelinTensorCompartment Models
ZeppelinStickAstrosticksMulti-Compartment ModelsMapping axon diameter and density in the living human brain with ActiveAx (Alexander et al, NeuroImage 2010)Fixed tissue: Vervet monkey 4.7T; 140mT/mIn vivo: human volunteer 3T; 60mT/m
Mapping neurite orientation dispersion and density with NODDI (Zhang et al, NeuroImage 2012)
OrientationDispersion
01NeuriteDensity
01CSF
01
01FractionalAnisotropyDominantOrientationDTINODDIThe acquisition protocol is simple to implement and clinically feasible.Neurite density: a potential imaging marker for brain recovery (Wang et al, PLoS One 2013)NODDI enables the extension of this animal model study to living human subjects.
Inference
NormalizationPipeline for advanced diffusion MRI analysis
Imaging
LocalizationDiffusion MRI supports superior anatomical alignment of white matter structures
DTI?T1Arcuate FasciculusOptic RadiationCorpus CallosumDTI-TK provides the state-of-the-art for aligning diffusion MRI dataRanked the best performing tool of its kind (Wang et al, NeuroImage 2011)Supports unbiased longitudinal analysis of diffusion MRI data (Keihaninejad et al, NeuroImage 2013)The importance of tensor-based alignment for longitudinal processing (Keihaninejad et al, NeuroImage 2013)Tensor-based alignment improves specificity
The importance of tensor-based alignment for longitudinal processing (Keihaninejad et al, NeuroImage 2013)Tensor-based alignment improves sensitivity
NormalizationPipeline for advanced diffusion MRI analysis
Imaging
Localization
Inference
Typical Voxelwise Analysis
Tract-Specific AnalysisTract-specific analysis with DTI-TK (Yushkevich et al, NeuroImage 2008; Zhang et al, Medical Image Analysis 2010)Evaluate specific a priori hypotheses (e.g., ALS impairs only motor tracts)Reduce confounding effect of neighboring structuresPresent findings in the context natural to the structureSummaryCamino provides a rigorous platform fordeveloping and validating advanced diffusion MRI methodsapplying these methods to routine clinical research and practiceDTI-TK supports population-based analysis of diffusion MRI data byimplementing the state-of-the-art spatial normalization tooldelivering a statistical inference tool tailored specifically for white matterTogether, they deliver an end-to-end pipeline for advanced diffusion MRI analysisAcknowledgementColleagues atCMIC and MIG (UCL)Penn Image Computing and Science Laboratory (U Penn)Camino funding supportEU CONNECT consortium (www.brain-connect.eu)MS Society of Great Britain and Northern IrelandUCLH Biomedical Research Centre funded by NIHRDTI-TK funding supportNIH-NIBIB R03-EB009321NIH-NINDS R01-NS065347