Diffusion-MRI processing for group analysis
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1 Diffusion-MRI processing for group analysis Felix Renard IRMaGe: Inserm US 17 / CNRS UMS 3552 University Hospital of Grenoble - France 25/09/2015 felixrenard@gmail.com 1
2 Diffusion-MRI processing for group analysis Why? - To search for differences between groups - To discover potential bio-markers How? - First-level : subject processing - Second-level : group processing
3 Diffusion-MRI processing for group analysis Diffusionnist: - Diffusion-MRI processing software - For normal population and for lesioned pathologies (stroke) - For clinical research (no batch and no lines of code) - Based on robust softwares (FSL and DTK/TrackVis) - Works on linux (Ubuntu distribution)
4 Diffusion-MRI processing for group analysis
5 Diffusion-MRI processing for group analysis Diffusionnist the pipeline:
6 Diffusion-MRI processing for group analysis Diffusionnist the pipeline: : -Multi group and longitudinal design -Possibility to analyse single subjects
7 One patient Global study folder Hierarchical data structure
8 Longitudinal study
9 Multi-subject study Longitudinal study
10 Multi-subject study Multi-group study
11 Data Folder Raw data (PAR/REC or Dicom) Diffusion Weighted Images (DWI) Tested on Philips and Siemens Specific to Lesion processing
12 Diffusion-MRI processing for group analysis Diffusionnist the pipeline: : - Motion artifacts & eddy current correction - Diffusion coefficient estimation ex: FA, MD, radial and axial diffusivity - Tractography estimation
13 : Motion artifacts - Motion artifacts (rotation and translation) - Correction by affine transformation. Small rotation DWI-7 DWI-8 DWI-9 DWI-10 DWI-11 DWI-12
14 : Eddy current correction - Distorsions due to eddy currents. (caused by fast commutation of the high amplitudes diffusion gradients ) - Correction by affine transformation [Poupon, 1999] [Mangin, 2001][Anderson, 2001] Achieved by FSL
15 : Diffusion coefficients estimation Fractional Anisotropy (FA) Mean Diffusivity (MD) Parallel Diffusivity (D// ) Perpendicular Diffusivity (D )
16 : Diffusion coefficients estimation QUALITY CHECK of the DATA!!! Inspect manually the data! Correct automatically the data (image and gradients table)!
17 : Diffusion coefficients estimation Fractional Anisotropy (FA) Mean Diffusivity (MD) Parallel Diffusivity (D// ) Perpendicular Diffusivity (D )
18 : Diffusion coefficients estimation CHECK your GRADIENT TABLES!!! Correct automatically the gradients table for all images! Inspect manually the data!
19 : Diffusion coefficients estimation Fractional Anisotropy (FA) Mean Diffusivity (MD) Parallel Diffusivity (D// ) Perpendicular Diffusivity (D )
20 : Tractography estimation Possibility to analyse the results with TrackVis!
21 Diffusion-MRI processing for group analysis Diffusionnist the pipeline: : - Linear and non linear registration - Registration considering lesions!!!
22 Why? FA patients FA template
23 How? From Collins,MNI REGISTRATION = estimation of a transformation T = rotation, scaling, translation (global deformation) D = High order transformation (local deformation)
24 Exemple Source Linear T Non linear D MNI space Patient space Target
25 Registration A synthetic exemple with lesion Ground truth Linear registration Without mask With mask Non linear registration Without mask With mask
26 Registration A synthetic exemple with lesion Ground truth Linear registration Without mask With mask Non linear registration Without mask With mask
27 Registration A synthetic exemple with lesion Ground truth Linear registration Without mask With mask Non linear registration Without mask With mask For lesioned brains, masks must be considered!
28 Registration Without mask With mask For lesioned brains, masks must be considered!
29 Diffusion-MRI processing for group analysis Diffusionnist the pipeline: : - TBSS - ROI analysis
30 TBSS 1) Non-linear registration, followed by 2) projection onto an alignment-invariant tract representation (the mean FA skeleton )
31 TBSS 1) Non-linear registration, followed by 2) projection onto an alignment-invariant tract representation (the mean FA skeleton )
32 TBSS with lesion Correct non linear registration Biased non linear registration
33 ROI analysis - the ICBM-DTI-81 white-matter labels atlas - created by hand segmentation - 48 white matter tract labels Exist others atlas Ex : natbrainlab Catani M, Jones DK, Donato R, ffytche DH. Occipito-temporal connections in the human brain. Brain 2003
34 ROI analysis
35 ROI analysis Use the skeleton to avoid partial volume
36 ROI analysis - 46 text files (for 46 ROIs) for each group for one coefficient - Column for times and row for subjects
37 Diffusion-MRI processing for group analysis Diffusionnist the pipeline: processing: - R,SPSS
38 analysis No specific algorithm is provided! Lot of softwares available (SPM, SPSS, R, Python, etc...)
39 Take home message All steps are important to have reliable results! Need to check all the steps! Be careful when process pathological brain imaging!
40 Questions?
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