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

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25/19/2015 Outline Nuclear Magnetic resonance (NMR) Diffusion Tensor Imaging (DTI) DTI-Based Connectivity Mapping Research in DTI

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Nuclear Magnetic Resonance

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45/19/2015 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. = B 0

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55/19/2015 Nuclear Magnetic Resonance Injection of Radio frequency pulse Free Induction decay Rotating frame of reference T1 relaxation T2 relaxation

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65/19/2015 Nuclear Magnetic Resonance MR gradients Slice Selection Multiple slices

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75/19/2015 Nuclear Magnetic Resonance κ-space Composed of sines and cosines Detail and frequency relation Image Reconstruction

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85/19/2015 Nuclear Magnetic Resonance Fourier Imaging Phase encoding Frequency Encoding MR sequence Parameters Repetition time Echo time Sampling time

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95/19/2015 Nuclear Magnetic Resonance Image contrast Hydrogen spin densities (N[H]) Longitudinal recovery times(T1) Transverse relaxation times (T2) Inherent Tissue Contrast Flow Magnetic Susceptibility Inhomogeneity Chemical Shift Noise Statistical noise: Eddy currents Systematic noise : Patient motion

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105/19/2015 MRI machines MRI Types Conventional MRI Open MRI (Regular, Standup) MRI Scans T1 and T2 Weighted Functional Diffusion HARP GRAPPA

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Diffusion Tensor Imaging

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125/19/2015 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

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135/19/2015 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.

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145/19/2015 Diffusion Tensor Imaging (DTI) Brain Tissue types Cerebrospinal fluid (CSF) Gray matter (GM) White matter (WM) Mixing of tissues

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155/19/2015 Diffusion Tensor Imaging (DTI) Invariant Anisotropy Indices Fractional Anisotropy (FA) * Relative Anisotropy (RA) * Volume Ratio (VR) * * D. LeBihan, NMR Biomed icine., 2002.

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165/19/2015 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.

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175/19/2015 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

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DTI-Based Connectivity Mapping

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195/19/2015 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.

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205/19/2015 DTI-Based Connectivity Mapping * Line Propagation Algorithms. Global energy Minimization Fast Marching Technique Simulated annealing approach * S.. Mori et. al, NMR IN BIOMEDICINE, 2002.

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215/19/2015 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.

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225/19/2015 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

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235/19/2015 Orientation Distribution function

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245/19/2015 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

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Thank You!

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