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Diffusion Tensor MRI And Fiber Tacking

Diffusion Tensor MRI And Fiber Tacking. Presented By: Eng. Inas Yassine. i.yassine@k-space.org. Outline. Nuclear Magnetic resonance (NMR) Diffusion Tensor Imaging (DTI) DTI-Based Connectivity Mapping Research in DTI. Nuclear Magnetic Resonance. Nuclear Magnetic Resonance.

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Diffusion Tensor MRI And Fiber Tacking

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  1. Diffusion Tensor MRI And Fiber Tacking Presented By: Eng. Inas Yassine. i.yassine@k-space.org

  2. Outline • Nuclear Magnetic resonance (NMR) • Diffusion Tensor Imaging (DTI) • DTI-Based Connectivity Mapping • Research in DTI

  3. Nuclear Magnetic Resonance

  4. Nuclear Magnetic Resonance • Magnetic resonance phenomenon • Nucleus acts as a tiny bar magnet • In the absence of external magnetic field, such tiny magnets are arranged randomly • Net magnetization at steady state = 0 • In the presence of a strong magnet field, tiny magnets tend to align along the field • Probability can be computed from Boltzmann ratio • Nonzero net magnetization results • Precession frequency given by Larmor Eqn.  =  B0

  5. Nuclear Magnetic Resonance • Injection of Radio frequency pulse • Free Induction decay • Rotating frame of reference • T1 relaxation • T2 relaxation

  6. Nuclear Magnetic Resonance • MR gradients • Slice Selection • Multiple slices

  7. Nuclear Magnetic Resonance • κ-space • Composed of sines and cosines • Detail and frequency relation • Image Reconstruction

  8. MRI machines • MRI Types • Conventional MRI • Open MRI (Regular, Standup) • MRI Scans • T1 and T2 Weighted • Functional • Diffusion • HARP • GRAPPA

  9. Diffusion Tensor Imaging

  10. Diffusion Tensor Imaging (DTI) • MR signal is attenuated as a result of diffusion • Brownian motion in the presence of gradients • Gradients are applied in different directions and attenuation is measured • DTI reconstruction using linear system solution

  11. Diffusion Tensor Imaging (DTI) • Mobility in a given direction is described by ADC • The tissue diffusivity is described by the tensor D • The diffusion equation • Diffusion is represented by a 33 tensor* *P. Basser and D. Jone, NMR in Biomedicine, 2002.

  12. Diffusion Tensor Imaging (DTI) • Brain Tissue types • Cerebrospinal fluid (CSF) • Gray matter (GM) • White matter (WM) • Mixing of tissues

  13. Diffusion Tensor Imaging (DTI) • Invariant Anisotropy Indices • Fractional Anisotropy (FA)* • Relative Anisotropy (RA)* • Volume Ratio (VR)* *D. LeBihan, NMR Biomedicine., 2002.

  14. Diffusion Tensor Imaging (DTI) • Single Tensor estimation • Estimation of direction is severely affected in the presence of noise* *X. Ma, Y. Kadah, S. LaConte, and X. Hu, Magnetic Resonance in Medicine, 2004.

  15. Source of noise in diffusion MRI • Statistical Noise • Magnetic Filed unhomogeneity • Eddy currents • Thermal Noise • background signals caused by precessing tissue magnetization. • Systematic Noise • from a number of patient motion, such as respiration, vascular, and CSF pulsations; • receiver-coil or gradient-coil motion; aliasing; and data truncation (Gibbs) artifacts

  16. DTI-Based Connectivity Mapping

  17. DTI-Based Connectivity Mapping • Nerve fibers represent cylindrical-shaped physical spaces with membrane acting like a barrier • DT shows diffusion preference along axon • Measuring the diffusing anisotropy, we can estimate the dominant direction of the nerve bundle passing through each voxel *X. Ma, Y. Kadah, S. LaConte, and X. Hu, Magnetic Resonance in Medicine, 2004.

  18. DTI-Based Connectivity Mapping* • Line Propagation Algorithms. • Global energy Minimization • Fast Marching Technique • Simulated annealing approach *S.. Mori et. al, NMR IN BIOMEDICINE, 2002.

  19. Limitations* • Inaccuracy of Single Tensor Estimation due to • Intravoxel Orientational Heterogeneity (IVOH). • Contribution from multiple tensors. • Limited signal to noise Ratio. • There may not be a single predominant direction of water diffusion. • Afferent and efferent pathways of axonal fiber tracts cannot be judged. *S.. Mori et. al, NMR IN BIOMEDICINE, 2002.

  20. Problem Statement • Partial voluming is common in practice • Attenuation due to multi-component diffusion when applying a gradient defined by the diffusion direction is given by, • It is required to estimate the component tensor and their partial volume ratios • 13 unknown for a 2-component model without loss of generality. • Nonlinear equations unlike 1-component case

  21. Orientation Distribution function

  22. Research in DTI • To develop Image denoising Algorithms diffusion Tensor MRI. • To develop a technique that would allow multiple diffusion components to be computed within a given voxel. • To predict the behavior of this technique under different conditions of SNR. • Improve diffusion orientation distribution function. • Probabilistic fiber tracking that satisfies the anatomical conditions

  23. Thank You!

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