Camino and DTI-TK: Advanced Diffusion MRI Pipeline for Traumatic Brain Injury

1. UCL Centre for Medical Image Computing 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

3. Virtual Histology Tissue Tissue Modeling Signal Estimate Predict Cell size, shape, density Diffusion MRI quantify water mobility in tissue Histology Model parameters are the tissue microstructure feature themselves! Membrane permeability Diffusion MRI Orientation distribution Axer, J. Neuro. Meth. 1999 Microstructure imaging with diffusion MRI

4. Imaging Localization Inference Normalization Pipeline for advanced diffusion MRI analysis

5. Imaging Localization Inference Normalization Pipeline for advanced diffusion MRI analysis

6. 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

7. Available Substrates Gamma-Distributed Radii Mesh-based substrates Crossing Cylinders Permeable Cylinders Monte Carlo Diffusion Simulator (Hall and Alexander, IEEE TMI 2009) Diffusion Substrate Displacement PDF Diffusion MR Signal Simulation Pipeline

8. Multi-Compartment Models Compartment Models Stick Astrosticks Ball Cylinder Zeppelin Astrocylinders GDRCylinders Tensor Sphere Dot ZeppelinStickAstrosticks Rich hierarchy of analytic models of diffusion MRI (Panagiotaki et al, NeuroImage 2012)

9. 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

10. 0 Orientation Dispersion 0 0 CSF Fractional Anisotropy 0 Neurite Density 1 1 1 1 Mapping neurite orientation dispersion and density with NODDI (Zhang et al, NeuroImage 2012) NODDI DTI Dominant Orientation The acquisition protocol is simple to implement and clinically feasible.

11. 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.

12. Imaging Localization Inference Normalization Pipeline for advanced diffusion MRI analysis

13. ? Corpus Callosum Optic Radiation Arcuate Fasciculus Diffusion MRI supports superior anatomical alignment of white matter structures T1 DTI

14. 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)

15. The importance of tensor-based alignment for longitudinal processing (Keihaninejad et al, NeuroImage 2013) Tensor-based alignment improves specificity

16. The importance of tensor-based alignment for longitudinal processing (Keihaninejad et al, NeuroImage 2013) Tensor-based alignment improves sensitivity

17. Imaging Localization Inference Normalization Pipeline for advanced diffusion MRI analysis

18. Typical Voxelwise Analysis Tract-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

19. 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

20. 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) • 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