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Diffusion Tensor Imaging Tim Hughes & Emilie Muelly 1
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DTI Module Learning objectives – Acquisition – Fiber orientation distribution function (ODF) – Tractography Projects – Combining fMRI + DTI to explore face recognition & working memory – Comparing and contrasting DTI parameters 2
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Diffusion Tensor Imaging DTI acquisition: – Non-diffusion weighted images – Diffusion weighted images (DWI) Magnitude of diffusion weighting (e.g. b=1200 or 2400) b-value : angular resolution signal:noise Output measures – Apparent Diffusion Co-efficient, Mean Diffusivity – Fractional Anisotropy (FA) 3
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Acquired b0 image Acquired b0 (b=0 s/mm 2 ): a reference for DTI analysis Problematic with partial volumes – Neuronal tissue – Free water (cerebrospinl fluid, extracellular fluid, and edema) Effect on ADC, FA value, and fiber tracking Partially fixed by FLAIR, – Incomplete saturation (mainly corrects for CSF) – Increased scan time 4
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Synthetic b0 Developed as a result of last year’s MNTP (Jung et al) Uses max signal intensity (from any direction) at each voxel to create synthetic b0 image Designed to minimize free water effect No impact on scan time R = max(DW images) (Image contrast enhanced using gamma corection: gamma=0.5)
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Tensor model – Single orientation at voxel (single ODF) – 6+ directions with 1 b0 – No information regarding fiber crossing Constrained Spherical Deconvolution (CSD) – HARDI (high angular resolution diffusion imaging) – 23+ DW directions with multiple b0 – Informative crossing Fiber ODF Analysis Methods Tournier et al., 2007 6
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Methods: Acquisition & Pre-prossessing 4 subjects Acquire diffusion weighted images – Siemens 3T MRI; TR = 6900ms, TE = 115ms – 50 directions, 5 b0 values (across time) – b-values = 1200 s/mm 2 or 2400 s/mm 2 – 2 acquisitions per subject, per b-value Pre-process the data: – Motion correction (rotation of vector table) – Create Synthetic b0 7
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Methods: ODF and Tractography ExploreDTI v4.8.0 (A. Leemans) ODF analysis (Tensor or CSD) Identified tracts using regions of interest Obtained tract-based statistics (mean FA value, standard deviation, number of “fibers”) 8 Fornix Cingulum Uncinate Fasciculus (UF) Inferior fronto-occipital fasciculus (IFOF)
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Methods: Fiber analysis Parameters – Diffusion weighting: – b0 images: – ODF method: SAS v9.2 – GLM, compare effects of each parameter on outcomes – Evaluated effects of all first order interactions on outcomes 9 Number of fibers Mean FA value b1200vs.b2400 Acquiredvs.Synthetic DTIvs.CSD
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Raw Data (UF) Synthetic b0Acquired b0 Tensor b2400 CSD b2400 Right_UF tensor b2400 acq b0 b2400 synthb0 b1200 acq b0 b1200 synth b0 FA value0.450.700.490.73 Std Dev0.120.100.130.10 # fibers3465353050175023 10 Right_UF CSD b2400 acq b0 b2400 synth b0 b1200 acq b0 b1200 synth b0 FA value0.340.600.430.66 Std Dev0.140.150.130.14 # fibers6345416255195455
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Effect of DTI parameters on number of fibers p-valueR² Subject0.09225% Tracts*<0.000170% b1200 vs. b24000.77020% Acquired b0 vs. Synthetic b0*0.73570% Tensor vs. CSD0.00416% 11 * Tract-based analysis indicates that synthetic b0 significantly increases the number of fibers in the fornix only.
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Effect of DTI parameters on mean FA value p-valueR² Subject0.90770% Tract*<0.000117% b1200 vs. b24000.12392% Acquired b0 vs. Synthetic b0*<0.000167% Tensor vs. CSD0.00138% Number of fibers 0.00466% 12 (positive correlation) * Significant interaction between b0 method and tract on mean FA value
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Mean FA value 13 mean FASD acquired 0.490.09 synthetic 0.650.06 Effect of Synthetic b0 on FA Value Differences by Tract
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Conclusions Changing DTI parameters can significantly alter the number of fibers and FA values Diffusion weighting – No significant differences in b1200 and b2400 b0 images – Synthetic b0 FA compared to acquired b0 – Effects of both FA and # fibers are most dramatic in the fornix ODF methods – CSD method # fibers, mean FA values compared to tensor based method 14
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Acknowledgments MNTP program – Seong-Gi Kim – Bill Eddy – Tomika Cohen DTI module Mentor – Kwan-Jin Jung TA – Xiaohan Huang 15
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