NA-MICNational Alliance for Medical Image Computing http://na-mic.org
fMRI Data Analysis in Slicer(short dataset tutorial)
Steve Pieper
Haiying Liu
Wendy Plesniak
Sandy Wells
Cindy Wible
Carsten Richter
National Alliance for Medical Image Computing http://na-mic.org
Acknowledgments
National Alliance for Medical Image ComputingNIH U54EB005149
Neuroimage Analysis Center NIH P41RR013218
FIRST Biomedical Informatics Research Network NCRR/NIH 5 MOI RR 000827
Harvard Center for Neurodegeneration and Repair
Data was acquired on a Philips Achieva 3T scanner. Courtesy of the Brain Imaging Laboratory, Dartmouth Medical School, a participating NAMIC site.
National Alliance for Medical Image Computing http://na-mic.org
Disclaimer
It is the responsibility of the user of 3DSlicer
to comply with both the terms of the license
and with the applicable laws, regulations
and rules.
National Alliance for Medical Image Computing http://na-mic.org
Goal of the tutorial
Guiding you step by step through the process of using the fMRIEngine to analyze fMRI data and visualize results within Slicer.
National Alliance for Medical Image Computing http://na-mic.org
Prerequisites
This tutorial assumes that you have already completed Slicer Basics:
• Loading and Viewing Data (Slicer Training 1)• Saving Data ( Slicer Training 7)
Supporting material: www.na-mic.org/Wiki/index.php/Slicer:Slicer2.6_Getting_Started
National Alliance for Medical Image Computing http://na-mic.org
Module current status
The fMRIEngine is:
• A package for analyzing and visualizing brain activations in Slicer’s multi-modality environment.
• a developing framework for a suite of activation detection algorithms and inference engines; currently it provides a basic linear modeling detector only.
• a prototype under development; it does not yet have full save/load functionality or full compatibility with other fMRI packages.
National Alliance for Medical Image Computing http://na-mic.org
Computer Resources• The short-dataset tutorial teaches you how the
module works; it uses a truncated fMRI timeseries to get users quickly familiar with the interface and workflow ( we recommend at least 1GB RAM).
• The full-dataset tutorial guides you through a full fMRI analysis. For this part, your computer must have adequate processing speed and RAM (we recommend at least 3GB).
Please use the appropriate tutorial and dataset for you.
National Alliance for Medical Image Computing http://na-mic.org
Tutorial datasetsDownload: fMRIEngineTutorial.zip www.na-mic.org/Wiki/index.php/Slicer:Workshops:User_Training_101
Short dataset: functional scans (file format Analyze):
functional01.hdr, functional01.img … functional90.hdr, functional90.img structural scan (file format NifTI): anatomical3T.hdr, anatomical3T.img
Full dataset: functional scans (file format Analyze): functional01.hdr, functional01.img … functional90.hdr, functional90.img structural scan (file format NifTI): anatomical3T.hdr, anatomical3T.img
National Alliance for Medical Image Computing http://na-mic.org
Tutorial datasets
What loaded data looks like:
• Functional scans………….(functional01.img)
• Structural scan ..………….(anatomical3T.img)
National Alliance for Medical Image Computing http://na-mic.org
Data description
Functional (EPI): 45 slices, 90 scans; 3.75 x 3.75 x 3.75 mm3 voxels (64 x 64 matrix with 240mm FOV). Transverse acquisition.
Preprocessing: realigned, motion corrected, normalized to MNI, smoothed.
Structural (MPRAGE): 170 sagittal slices; 1x1x1.2 mm3 voxels; normalized to MNI.
National Alliance for Medical Image Computing http://na-mic.org
ParadigmFinger sequencing fMRI task• Blocked motor paradigm• Subject alternates simple left and right thumb to finger sequencing
(always same thumb to 1,2,3,4 finger order within block).• Three cycles each of rest, right hand and left hand.
TR = 2 secondsDurations: 10 TRs in all epochsOnsets (in TRs):
Rest: 0 30 60 Right : 10 40 70 Left : 20 50 80
National Alliance for Medical Image Computing http://na-mic.org
Slicer’s fMRIEngine
National Alliance for Medical Image Computing http://na-mic.org
fMRIEngine workflowLoad preprocessed functional data
Describe paradigm and stimulus schedule
Specify linear modeling & estimate model parameters
Define contrasts and compute parametric map
Statistical inference
inspect data & combine with other analyses
National Alliance for Medical Image Computing http://na-mic.org
Overview
Part 1: Loading and Previewing Data
Part 2: Describing stimulus schedule
Part 3: Linear modeling & estimation
Part 4: Contrasts & computing SPMs
Part 5: Inference & inspection
National Alliance for Medical Image Computing http://na-mic.org
Load Image Sequence
1: Pick Sequence->Load tab
7: Click Apply
2: Click File Browse
6: Input a sequence name
5: Input a file filter
4: Click Load Multiple Files
3: Pick any file in thefunctional directory
National Alliance for Medical Image Computing http://na-mic.org
Set Image Display
11: operations will apply to currently viewed image in the sequence only…
8: Go to Volumes->Display
9: Adjust Win and Lev to get best displayof image data
10: Adjust Lo threshold to mask out non-brain
National Alliance for Medical Image Computing http://na-mic.org
Select Image Sequence
13: Pick Select Tab
14: Specify number of runs = 1
15: Click Add toassign sequence to run 1
16: Click Set Window/Level/Thresholdsto apply to all volumes inthe sequence
12: Go back to fMRIEngine
Visually inspect sequence
National Alliance for Medical Image Computing http://na-mic.org
Overview
Part 1: Loading and Previewing Data
Part 2: Describing stimulus schedule
Part 3: Linear modeling & estimation
Part 4: Contrasts & computing SPMs
Part 5: Inference & inspection
National Alliance for Medical Image Computing http://na-mic.org
Stimulus schedule
16: Pick Set Up Tab and choosethe Linear Modeling detector
17: Choose Paradigm Design
18: Enter schedule for first condition(name = right)
19: Click OK to add this conditionto the list of defined conditions
}
detection technique
linear modeling step
National Alliance for Medical Image Computing http://na-mic.org
Stimulus schedule
20: Enter schedule for nextcondition (Name = left)
21: Click OK to add this conditionto the list too…
}
National Alliance for Medical Image Computing http://na-mic.org
Stimulus schedule
22: To change the schedule forany condition: select condition from box, click Edit, make changes,and click OK again to re-assign it.
23: To delete any defined condition: select it and clickDelete
Making modifications…
After clicking OK, each specified condition for Run 1 is listed as shown below, labeled “r1:condition_name”
National Alliance for Medical Image Computing http://na-mic.org
Overview
Part 1: Loading and Previewing Data
Part 2: Describing stimulus schedule
Part 3: Linear modeling & estimation
Part 4: Contrasts & computing SPMs
Part 5: Inference & inspection
National Alliance for Medical Image Computing http://na-mic.org
Model Signal
24: Choose the Signal Modeling step
25: Click to model both conditions identically
28: model drift with Discrete Cosine set
27: convolve with HRF
30: Add to Model26: choose boxcar waveform
29: Choose to use default cutoff
National Alliance for Medical Image Computing http://na-mic.org
View Design Matrix
31: Click View Design
32: The model design matrix appears in a separate window(this may take some time)
National Alliance for Medical Image Computing http://na-mic.org
Estimating model parameters
33: Choose the estimation step
34: Select run1 and click Fit Model
National Alliance for Medical Image Computing http://na-mic.org
Overview
Part 1: Loading and Previewing Data
Part 2: Describing stimulus schedule
Part 3: Linear modeling & estimation
Part 4: Contrasts & computing SPMs
Part 5: Inference & inspection
National Alliance for Medical Image Computing http://na-mic.org
Specify Contrasts
35: Choose Contrasts step
36: Specify Name (c1)37: Name activation volume38: Specify contrast vector (1 –1 0 0)39: Click OK to add this contrast to a list of defined contrasts
40: Contrast name appears here
National Alliance for Medical Image Computing http://na-mic.org
Check contrasts & model
41: Click View Design
42: Verify contrast is correct
National Alliance for Medical Image Computing http://na-mic.org
Perform activation detection
43: Select Detect tab
44: Select contrast to compute for
45: Click Compute
National Alliance for Medical Image Computing http://na-mic.org
Overview
Part 1: Loading and Previewing Data
Part 2: Describing stimulus schedule
Part 3: Linear modeling & estimation
Part 4: Contrasts & computing SPMs
Part 5: Inference & inspection
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
46: Pick View Tab
47: Select activation volume
48: Click Select
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
49: Pick Threshold Tab
50: Select uncorrected p-value
51: Specify p-value threshold = 0.001
Activations appear in the foreground
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
Display anatomical image in background
Color map code:Strong negative activation
Below p-value threshold (not rendered)
Weak negative activation
Weak positive activation
Strong positive activation
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
52: Pick Plot tab
53: Select condition = right
54: Select Timecourse plot option
Plotting…
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
55: Mouse over labeled voxelin Slice Window and click…
view voxel’s timecourse plotted with the modeled condition
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect56: Select Peristimulus histogram option and click a voxel labeled as active
57: Click any curve on the peristimulus plot for details
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
58: Select ROI tab
59: Choose New from label map pulldown menu…
Activation-based Regions of Interest…
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
60: Click Create label map…
61: Wait short while while activation “blobs” are labeled
62: Default blob view:Label map shown in FG; activation map shown in BG.
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
63: Select Stats tab
64: Select one or multiple regions to include in analysis by clicking in Slice Window. Selected regions display green.
65: (clear all selections and start over if you make a mistake)
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
66: Click Show stats
View region statistics
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
67: Select Timecourse plot option
68: Click Plot time series for this region
View region statistics
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
69: Select Peristimulus histogram option
70: Click Plot time series for this region
View region statistics
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
72: Fade in the activation volume a little more for agood view of combined data
71: Clear selections.
Then display anatomical image in BG and activation in FG.
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
Adjusting colormaps for visualization…
73: Navigate to Volumes->Display
74: Set the Active Volume to be the activation volume
75: Adjust Window and Level to shift the color map hue range
Recall color map code:Strong negative activation
Below p-value threshold (not rendered)
Weak negative activation
Weak positive activation
Strong positive activation
National Alliance for Medical Image Computing http://na-mic.org
Threshold, visualize, inspect
To view only positive activations…
76: Choose Palette to be fMRIPosActive
75: Adjust Window and Level to shift the color map hue range
Color map code:
Below p-value threshold (not rendered)
Weak positive activation
Strong positive activation
National Alliance for Medical Image Computing http://na-mic.org
Features to come…
Features that will be developed within the fMRIEngine:
• Load/Save functionality for modeling and analysis
• Ability to apply prior models
• Ability to perform other statistical tests
• Other techniques for performing activation detection
• Advanced visualization
• …
Top Related