DTI Primer.pdf - The Gabrieli Lab at MIT
DTI Primer.pdf - The Gabrieli Lab at MIT
DTI Primer.pdf - The Gabrieli Lab at MIT
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<strong>DTI</strong> Study AcrossDevelopmentElizabeth Gutierrez8.29.2010
Wh<strong>at</strong> is <strong>DTI</strong>?• Diffusion Tensor Imaging• Imaging method th<strong>at</strong> uses thediffusion of w<strong>at</strong>er to assess whitem<strong>at</strong>ter in the brain.
Diffusion Tensor ImagingConcept Behind <strong>DTI</strong>
Concept Behind <strong>DTI</strong>Brownian MotionDiffusion Tensor ImagingIsotropy
Concept Behind <strong>DTI</strong>Axon BundleDiffusion Tensor Imaging
Concept Behind <strong>DTI</strong>Axon BundleDiffusion Tensor ImagingAnisotropy
<strong>The</strong> Diffusion TensorScalar Vector TensorOne dimension Two dimensions Three dimensionsDiffusion Tensor Imaging
<strong>The</strong> Diffusion Tensor6 DirectionsEigen-valuesEigen-vectorsTensorThree dimensionsDiffusion Tensor Imaging“Correspond to the main diffusiondirections and associ<strong>at</strong>eddiffusivities”Le Bihan, et al., 2001
Extracting Inform<strong>at</strong>ionMeanDiffusivityMDOverallDiffusivityDiffusion Tensor ImagingFractionalAnisotropyFAIndex th<strong>at</strong>reflects degree ofdirectionality
Extracting Inform<strong>at</strong>ionMeanDiffusivityMDOverallDiffusivityDiffusion Tensor ImagingFractionalAnisotropyFAIndex th<strong>at</strong>reflects degree ofdirectionality
Extracting Inform<strong>at</strong>ionMeanDiffusivityMDOverallDiffusivityDiffusion Tensor ImagingFractionalAnisotropyFAIndex th<strong>at</strong>reflects degree ofdirectionality
Imaging (Applic<strong>at</strong>ions)Brain White M<strong>at</strong>terBrain Connectivity-Loc<strong>at</strong>ion of axonal tracts-White m<strong>at</strong>ter density-Myelin fiber integrity- Tractography- Characterizeconnections betweenparts of the brain.Diffusion Tensor Imaging
Studies onWhite M<strong>at</strong>ter (WM)Development
Wh<strong>at</strong>? - Individual Differences in WMIn? - Declar<strong>at</strong>ive Memory, Ucin<strong>at</strong>e FasciculusUsing? - FA Value Correl<strong>at</strong>ion, ProbabilisticTractography and TBSS
<strong>The</strong>ir MethodsD<strong>at</strong>a Analysis*Probabilistic Tractography with FDT (for UF)Calcul<strong>at</strong>e mean FA, MD and eigen-values for ROIsCorrel<strong>at</strong>e values with age and behavioral scores*Use TBSS for voxel-wise st<strong>at</strong>istical analysis
<strong>The</strong>ir ResultsCorrel<strong>at</strong>ion betweenage/IQ and memory
<strong>The</strong>ir ResultsRel<strong>at</strong>ions between WM and Memory in Ucin<strong>at</strong>e FasciculusNo FAdifferencesNeg<strong>at</strong>iveCorr. with MDNeg<strong>at</strong>iveCorr. with2ndeigenvalueCorrel<strong>at</strong>ion betweenIndices and FreeRecall
<strong>The</strong>ir ResultsRel<strong>at</strong>ions between WM and Memory in WM compartmentsFA increases infrontal, parietaland temporalCorrel<strong>at</strong>ion betweenIndices and Age
<strong>The</strong>ir Results* *Positive MDcorrel<strong>at</strong>ionsCorrel<strong>at</strong>ion betweenIndices and memoryscores
<strong>The</strong>ir ResultsHierarchical Regressionfor Age and FA values
<strong>The</strong>ir ResultsTBSSCorrel<strong>at</strong>ionbetween recall andFA with TBSS
<strong>The</strong>ir ResultsLimit<strong>at</strong>ions/Consider<strong>at</strong>ionsAge as a continuousvariableIQ one SD above averageCross-SectionalNo Functional Correl<strong>at</strong>ionCan be addressed byusing Functional ROIs
Difference:<strong>The</strong>y use radial and axial diffusivitiesRadial - perpendicularAxial - parallel to axonto axon
<strong>The</strong>ir ResultsIncrease in FADecrease in MDDecrease in RDDecrease in AD-Attributed to growth of acomplex microstructureand glial cells duringdevelopment
Wh<strong>at</strong>? - WM DevelopmentIn? - Childhood/Adolescence (no behavior)Using? - SPM, FA values
<strong>The</strong>ir ResultsFA Changes with Age-in prefrontal regions-within and between basal ganglia-thalamusWM DensityChanges with Age- increases in internal capsule,inter-thalamic p<strong>at</strong>hways, andcorpus callosum
Difference:<strong>The</strong>y used ADC and not MDSame thing?
Observ<strong>at</strong>ion:Uses SPM to correl<strong>at</strong>e FA/MD with behavioral d<strong>at</strong>aDoesn’t present explicit FA/MD value
Regions where high FA is associ<strong>at</strong>ed with high delay
Correl<strong>at</strong>ion of selected FA clusters and AUC
Reviews:- WM in Cognitive Development- WM development as seen through <strong>DTI</strong>- in kids vs. adults; teens vs. adults-Sex differences in WM development- WM and Cognitive Function- IQ, working memory, inform<strong>at</strong>ion processing,reading
Wh<strong>at</strong> we have(Right Now)!
Example Subject - s100Index MapsFAMD1st 2nd 3rdEigen-Values
Example Subject - s100Index MapsLinesRGBV1 map overlaidwith FA mapGreyscale
Example Subject - s100BedpostX outputs“bedpostx runs Markov Chain Monte Carlo sampling to build up distributions ondiffusion parameters <strong>at</strong> each voxel.”mean_f1samples - mean of distribution of FA
Example Subject - s100ProbtrackX outputs“PROBTRACKX involves gener<strong>at</strong>ing connectivity distributionsfrom user-specified seed voxel(s). All brain voxels will have avalue representing the connectivity value between th<strong>at</strong> voxel andthe seed voxel (i.e., the number of samples th<strong>at</strong> pass through th<strong>at</strong>voxel).”Right Hippocampus seed mask
TBSS - Tract Based Sp<strong>at</strong>ial St<strong>at</strong>isticsGroup 1 (4 kids) vs. Group 2 (4 adults)1>2
Other Interesting Studies on <strong>DTI</strong> andConnectivity (Functional and Structural)
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