fmri Image Preprocessing

Transcription

1 fmri Image Preprocessing Rick Hoge, Ph.D. Laboratoire de neuroimagerie vasculaire (LINeV) Centre de recherche de l institut universitaire de gériatrie de Montréal, Université de Montréal

2 Outline Motion correction Spatial filtering Distortion correction Physiological noise correction

3 Motion Correction serial realignment of all images to a target volume average over all volumes a single early or middle volume motion parameters can be used in subsequent temporal filtering

4 Image series with motion

5 Translations 2 1 AP Signal (au) 0 LR HF Time (s)

6 Rotations 2 1 pitch Signal (au) 0 roll yaw Time (s)

7 Realigned Series

8 MRM 31: (1994)

9 Stimulus-correlated motion

10 Artifactual activation

11 fmri Bite Bar Moana-Filho et al. BMC Neuroscience 2010

12 Software Support all major fmri software packages provide motion correction FSL SPM AFNI etc...

13 Spatial Filtering random noise in fmri data has a fairly high amplitude, comparable to functional changes we seek to detect averaging adjacent voxels can help increase the signal-to-noise ratio typically a 3D Gaussian smoothing kernel with width of around 5-6 mm is applied

14 Noise in fmri data 2 mm in-plane resolution

15 Dependence of SNR on spatial resolution 4 mm in-plane resolution

16 2 mm

17 4 mm

18 Noise drives residual error in GLM Signal (au) Time (s)

19 Signal (au) mm Signal (au) mm

20 NeuroImage 32 (2006) Effect of spatial smoothing on physiological noise in high-resolution fmri Christina Triantafyllou, Richard D. Hoge, and Lawrence L. Wald* MGH/MIT/HMS A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Dept. of Radiology, Mailcode 2301, Bldg. 149, 13th Street, Charlestown, MA 02129, USA

21 Image noise vs. temporal noise Signal (au) Time (s) Image Temporal

22 Image SNR and voxel volume 1.5 Tesla 3 Tesla 7 Tesla

23 Temporal SNR and voxel volume 1.5 Tesla 3 Tesla 7 Tesla

24 Temporal Filtering typically carried out as part of statistical modelling low frequency drift residual motion effects physiological noise

25 Temporal filtering example response terms motion terms drift terms

26 Physiological Noise motion cardiac pulsation respiratory movement

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28 Image-Based Method for Retrospective Correction of Physiological Motion Effects in fmri: RETROICOR Gary H. Glover, 1 * Tie-Qiang Li, 1 and David Ress 2 Magnetic Resonance in Medicine 44: (2000)

29 Physiological noise in short-tr acquisition TR = 250 ms

30 Physiological noise in long-tr acquisition TR = 1 s

31 TR = 1 s

32 Reduction of residual error through physiological noise correction Raw K-Space correction Image-Space correction

33 NeuroImage 39 (2008) Physiological noise modelling for spinal functional magnetic resonance imaging studies Jonathan C.W. Brooks, a, Christian F. Beckmann, e Karla L. Miller, b Richard G. Wise, c Carlo A. Porro, d Irene Tracey, a,b and Mark Jenkinson b

34 TR = 250 ms

35 Image distortion and dropout Microscopic: deoxygenated hemoglobin Macroscopic air-filled sinuses

36

37 Field Mapping image magnetization pattern at different echo times allows calculation of field offset based on phase accrual per unit time can be used to correct for distortion, but not dropout

38 MRI Data is Complex Magnitude (used) M xy Phase (discarded) = tan 1 M y M x

39 Phase image - short TE

40 Phase image - long TE

41 Distortion vs. Dropout distortion is associated with large echospacing values in EPI readouts dropout is associated with large voxel dimensions the following slides illustrate that they are independent processes (even though both are caused by field inhomogeneities)

42 EPI over MPRAGE 2 mm

43 3 mm

44 4 mm

45 5 mm

46 EPI over MPRAGE 2 mm

47 3 mm

48 4 mm

49 5 mm

50 EPI over MPRAGE 2 mm

51 3 mm

52 4 mm

53 5 mm

54 Distortion Correction use of parallel imaging techniques to minimize EPI readout duration always acquire a field map only use 128 matrix EPI scans if you really need them

55 Avoiding Dropout simplest way to minimize dropout is by reducing voxel dimensions will require more smoothing to recover SNR other advanced techniques such as Z-shim may be used always check your EPI coverage by overlaying raw EPI scans on an MPRAGE

56 Typical Order of Operations motion-correction spatial smoothing linear modeling temporal filtering of drift and and residual motion as nuisance regressors distortion correction applied to effect-size estimates etc. prior to group GLM

57 Questions?