Presentation on theme: "Camino and DTI-TK: Advanced Diffusion MRI Pipeline for Traumatic Brain Injury Gary Hui Zhang, PhD Microstructure Imaging Group Centre for Medical Image."— Presentation transcript:
Camino and DTI-TK: Advanced Diffusion MRI Pipeline for Traumatic Brain Injury Gary Hui Zhang, PhD Microstructure Imaging Group Centre for Medical Image Computing Department of Computer Science University College London 26th of June, 2013 UCL Centre for Medical Image Computing
Microstructure imaging with diffusion MRI Estimate Predict Signal Diffusion MRI quantify water mobility in tissue Diffusion MRI Tissue Cell size, shape, density Membrane permeability Orientation distribution Axer, J. Neuro. Meth. 1999 Histology Tissue Modeling Model parameters are the tissue microstructure feature themselves! Virtual Histology
Camino: a platform for advanced diffusion MRI analysis Implements a rich hierarchy of analytic models for diffusion MRI Provides a robust framework for fitting diffusion MRI data to the models Delivers a sophisticated simulator for validating diffusion MRI models
Monte Carlo Diffusion Simulator (Hall and Alexander, IEEE TMI 2009) Available Substrates Gamma-Distributed Radii Crossing Cylinders Mesh-based substrates Permeable Cylinders Diffusion SubstrateDisplacement PDFDiffusion MR Signal Simulation Pipeline
Rich hierarchy of analytic models of diffusion MRI (Panagiotaki et al, NeuroImage 2012) Stick Cylinder GDRCylinders Ball Astrosticks Astrocylinders Sphere Dot Zeppelin Tensor Compartment Models ZeppelinStickAstrosticks Multi-Compartment Models
Mapping axon diameter and density in the living human brain with ActiveAx (Alexander et al, NeuroImage 2010) Fixed tissue: Vervet monkey 4.7T; 140mT/m In vivo: human volunteer 3T; 60mT/m
Mapping neurite orientation dispersion and density with NODDI (Zhang et al, NeuroImage 2012) Orientation Dispersion 01 Neurite Density 01 CSF 01 01 Fractional Anisotropy Dominant Orientation DTI NODDI The 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.
Diffusion MRI supports superior anatomical alignment of white matter structures DTI ? T1 Arcuate Fasciculus Optic Radiation Corpus Callosum
DTI-TK provides the state-of-the-art for aligning diffusion MRI data Ranked 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
Typical Voxelwise AnalysisTract-Specific Analysis Tract-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 structures Present findings in the context natural to the structure
Summary Camino provides a rigorous platform for developing and validating advanced diffusion MRI methods applying these methods to routine clinical research and practice DTI-TK supports population-based analysis of diffusion MRI data by implementing the state-of-the-art spatial normalization tool delivering a statistical inference tool tailored specifically for white matter Together, they deliver an end-to-end pipeline for advanced diffusion MRI analysis
Acknowledgement Colleagues at CMIC and MIG (UCL) Penn Image Computing and Science Laboratory (U Penn) Camino funding support EU CONNECT consortium (www.brain-connect.eu)www.brain-connect.eu MS Society of Great Britain and Northern Ireland UCLH Biomedical Research Centre funded by NIHR DTI-TK funding support NIH-NIBIB R03-EB009321 NIH-NINDS R01-NS065347