Siemens fMRI User manual

www.usa.siemens.com/healthcare
fMRI User Guide
Version 1.03

2fMRI User Guide
Important Note
This guide is for informational purposes only. Siemens does not endorse any specific third-party products that may
be mentioned in this guide. These third-party products have not been officially approved by Siemens, and have
been mentioned only as examples.
Acknowledgement
Special thanks to Paul Keselman, Dept. of Neuroscience, UCSF, for his help in writing this guide.
Table of Contents
1 PrerequisitesforRunningfMRIStudies .....................................................3
1.1 Licenses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3
1.1.1 VB13A,VB15A,VB15B,VB17A .....................................................3
2 Revisiting the BOLD Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
3 Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
3.1 EPI sequences for BOLD imaging. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
3.2 fMRIAcquisition .....................................................................6
3.2.1 Trigger out for synchronization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
3.2.2 GatinganEPIsequence..........................................................6
3.2.3 InterleavedslicereorderinginEPI..................................................6
3.2.4 Motioncorrection ..............................................................7
3.2.5 Difference between ep2d_pace and ep2d_bold sequences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
3.2.6 Analyzing data acquired using Motion Correction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
3.2.7 Accessing motion detection parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
3.2.8 Dummyscans .................................................................8
3.2.9 Slicetiming ...................................................................9
3.2.10 Slicetimecorrection............................................................9
3.2.11 Spatial filter specifications (conversion to mm) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
3.2.12 Co-registrationbetweendatasets.................................................10
3.3 fMRI data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
4 Peripherals ...........................................................................11
4.1 Responsepad ......................................................................11
4.2 Visualstimulus .....................................................................11
4.2.1 Projector .....................................................................11
4.2.2 LCD screen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
4.3 Auditory ..........................................................................13
4.4 Eyetracker.........................................................................13
4.5 Physiological monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
4.6 Synchronization ....................................................................14
4.7 Installingperipheraldevices...........................................................15
4.8 IdentifyingRFinterference............................................................16
4.8.1 RF noise tests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16
5 TypicalEPIArtifacts ....................................................................17
5.1 N/2ghosting.......................................................................17
5.2 Distortion .........................................................................18
5.3 Spatial image shifts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18
5.4 Chemical shift artifact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
6 SettingupabasicfMRIexperiment .......................................................19
6.1 Studydesign.......................................................................19
6.2 Running the study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

3fMRI User Guide
1 Prerequisites for Running fMRI Studies
1.1 Licenses
1.1.1 VB13A, VB15A, VB15B, VB17A
Application Package
• Licenses
– Features
Inline BOLD Imaging
• Inline BOLD Imaging
– Single Shot EPI for BOLD Imaging (ep2d_bold)
– Inline BOLD Processing: Paradigm, GLM (General Linear Model), Spatial Filter, ART (Advanced Retrospective
Technique)
– Mosaic Image Format
3D PACE
• 3D PACE
– 2D Single Shot EPI for BOLD-Imaging with 3D PACE (ep2d_pace)
BOLD 3D Evaluation
• MR BOLD Evaluation
– BOLD Evaluation Taskcard for Neuro3D Evaluation
– Evaluation with colored overlay representation
• MR 3D Offline fMRI
– Neuro3D Taskcard (Offline Modus)
– fMRI Offline Visualization and Analysis
• MR 3D Inline fMRI
– Inline functionality based on Neuro3D Taskcard

4fMRI User Guide
2 Revisiting the Bold Effect
fMRI uses the BOLD effect to detect neuronal activation. Let’s review the basic facts:
• Oxygen is delivered to the cells attached to hemoglobin
• Oxygenated hemoglobin is diamagnetic – very small magnetic moment
• Deoxygenated hemoglobin is paramagnetic – has a significant magnetic moment
On activation, stimulated tissue undergoes an increase in blood flow. This in turn:
• Increases the delivery of oxygenated hemoglobin
• Decreases the amount of deoxygenated hemoglobin within the tissue, thus reducing the concentration of
paramagnetic species
• Reduces the amount of susceptibility induced dephasing and therefore increases the T2* of the stimulated
tissue vs. the unstimulated tissue
• To detect these activations, brain activation studies are performed using T2* weighted sequences
• On a T2* image, the stimulated tissue will then have a brighter signal vs. the unstimulated tissue
Figure 1. Signal response from stimulated and unstimulated tissue. Increased blood flow and oxygenation
increases T2, and thereby the signal intensity in stimulated regions.
Signal
TE Time
Unstimulated tissue
Stimulated tissue

5fMRI User Guide
3 Sequences
3.1 EPI sequences for BOLD Imaging
The following sequences are available as options for acquiring BOLD sensitive images:
ep2d_fid
• Basic single-shot EPI sequence
ep2d_bold
• Single-shot EPI sequence with the BOLD imaging card • paradigm, GLM, t-test, spatial filter, etc.
ep2d_pace
• Single-shot EPI sequence with the BOLD imaging card – paradigm, GLM, t-test, spatial filter, etc. and prospective
motion correction
Here is a schematic of the EPI data acquisition scheme that is common to all three sequences:
Figure 2. Schematic of data acquisition scheme in EPI sequences. A fat suppression pulse (FS) is followed by a
single-shot acquisition of the acquisition of all the slices. The fat suppression and acquisition of all slices are then
repeated for the number of measurements desired. An optical trigger signal is generated for each measurement.
Optical
trig. out
FS = fat saturation
RF = radiofrequency pulse
PC = phase correction
Single-shot EPI Data acquisition
# of slides
# of measurements (volumes)
Spoil
RF
FS PC

6fMRI User Guide
3.2 fMRI Acquisition
3.2.1 Trigger Out for Synchronization
The EPI sequences generate an optical TRIGGER_OUT at the beginning of each volume (each measurement).
The TRIGGER_OUT pulse is of 10µs duration. This optical trigger signal is available at the U3 connection (only
applicable for Tim™ Systems) on the LWL-Int board in the cabinet. Please ask your service engineer for assistance
in locating this output. Typically, one needs to convert the optical signal to a TTL pulse in order to use it for
synchronizing scanner activity with other devices. An optical to TTL “fMRI Trigger Converter” may be purchased
from Siemens for this purpose. The output from this box is via a BNC or serial port. There are two different modes
of TTL output on this box – impulse mode or toggle mode. Refer to the converter box manual for details. Please
contact your local Inside sales representative to purchase this equipment.
3.2.2 Gating an EPI Sequence
The EPI sequence can be gated using either standard ECG or pulse triggering available through the scanner, or by
means of an external trigger from another device. The external trigger can be fed into the scanner via the cinch
jack trigger input on the left side of the front of the magnet cover. Of the two jacks, connect the external trigger
signal to the jack that has the following symbol:
For specification on the desired shape and amplitude of the trigger signal, please refer to the System Manual,
under “External Triggering.”
Note: The measurement is triggered by the rising edge of the external signal.
3.2.3 Interleaved Slice Reordering in EPI
If TOTAL # SLICES = EVEN, then the excitation order when “interleaved” is EVENS first, ODDS second, e.g.
2,4,6,8….. and then 1,3,5,7…..
If TOTAL # SLICES = ODD, then the excitation order when “interleaved” is ODDS first, EVENS second, e.g.
1,3,5,7….. and then 2,4,6,8…...

7fMRI User Guide
3.2.4 Motion Correction
MoCo checkbox controls motion correction in general. In the ep2d_pace sequence, if MoCo is not checked, no
motion correction is performed. Only the original EPI images are generated. If MoCo is selected, the following
functions are performed in MotionCorrDecorator (ICE):
• DetectMotion3D
• SendPACEFeedback (controlled by m_iPACE, set by sequence)
• CorrectMotion3D (write MoCo parameters to DICOM and log file)
If MoCo is not selected, then none of the above methods will be invoked. No motion correction takes place,
neither prospective nor retrospective.
ep2d_bold sequence:
MoCo ON: Retrospective motion correction, two series generated, original EPI series and MoCo series.
MoCo OFF: No motion correction, only original EPI series generated.
ep2d_pace sequence:
MoCo ON: Prospective motion correction, two series generated, original EPI series (if motion is detected in a
volume, all future volumes are prospectively corrected in this series) and a MoCo series (with those volumes in
which motion is detected, being corrected).
MoCo OFF: No motion correction, only original EPI series generated.
3.2.5 Difference between ep2d_pace and ep2d_bold sequences
The difference between ep2d_pace and ep2d_bold is mainly in the sequence. ep2d_pace retrieves the detected
motion parameters in DetectMotion3D() and uses it to turn the gradients with the head (so called prospective,
PACE). This now affects the original images, but only prospectively, i.e. only for the succeeding volumes.
Example:
Let’s say motion occurred in volume 23. Using PACE (ep2d_pace), volume 24 and following are turned with the
motion, but volume 23 is NOT affected in the original series. In the MoCo series, volume 23 is corrected using
CorrectMotion3D(). The following series do not need correction, since they are already acquired in the new tilted
patient frame.
Not using PACE (ep2d_bold), volume 24 and following still remain tilted in the original series. In the MoCo series,
volumes 23 and all the following are corrected.
3.2.6 Analyzing data acquired using Motion Correction
If the ep2d_pace sequence is used for acquiring data, and motion correction is checked ON, then one must use
the MoCo series (e.g. bas_MoCo, act_MoCo) for data analysis, not the EPI series.
If the ep2d_bold sequence is used, one may use the original EPI series or the MoCo series, depending on whether
one wants to use the original data or retrospectively corrected data.

8fMRI User Guide
3.2.7 Accessing Motion Detection Parameters
From the above explanation, it is obvious that there is only one set of motion parameters. The difference lies in
whether they are used for prospective or retrospective motion correction. The motion parameters can be found
under:
VB15: C:\Medcom\MCIR\Med\SimMeasData\MotionDetectionParameter.txt
VB13: C:\MRIR\Med\SimMeasData\MotionDetectionParameter.txt
VB12 and older baselines: C:\MedCom\Temp\MotionDetectionParameter.txt
3.2.8 Dummy scans
Figure 3. Schematic showing how the dummy cycles are performed in the EPI pulse sequence. Assumptions:
TR = 2.5 s, iPAT= 2. Also, for simplicity, the number of slices is assumed to be 1. For a multislice protocol, the
sequence of events will be identical, except that there will be multiple RF pulses and EPI readouts per TR
(equal to the number of slices).
2 dummy scans (2 TRs)
no ADCs
FS
3-line
TR TR TR
EPI
RF
Gslice
Gread
Gphase
iPAT reference scan,
readout counted
at main TE if using <
max # reference lines main scan

9fMRI User Guide
If the number of measurements or averages is greater than one, dummy scans are used. The numbers of dummy
scans (used for stabilizing the signal) depend on the TR selected. The sequence takes the TR that is selected by
the user, and then calculates how many repeats (so-called “dummy scans” or prep scans) to run based on a FIXED
TIME of 3 seconds. No matter what the TR is, at least 1 dummy scan will always be performed. Then, based on the
TR as it compares to 3 seconds, any additional dummy scans are determined. Finally, if iPAT is selected, there are
one or more additional scans before data acquisition for acquiring the reference lines.
= 1 + quotient[ 3/TR(in seconds) ] if no iPAT
# of dummy scans = 1 + quotient[ 3/TR(in seconds) ] + 1 if iPAT = 2
= 1 + quotient[ 3/TR(in seconds) ] + 3 if iPAT = 3
= 1 + quotient[ 3/TR(in seconds) ] + 4 if iPAT = 4
e.g.
Example:
If TR is 1500 ms, 2 more dummy scans will be performed (total of 3 dummy scans).
If TR is 2500 ms, 1 more dummy scan will be performed (total of 2 dummy scans).
If TR is 3000 ms, 1 more dummy scan will be performed (total of 2 dummy scans).
If TR is 3001 ms, no more dummy scans will be performed (total of 1 dummy scan).
If TR is 3500 ms, no more dummy scans will be performed (total of 1 dummy scan).
After the dummy scans, there are 1 or more scans (TRs) to acquire iPAT reference lines, depending on what iPAT
factor is selected. In the EPI sequence, the iPAT reference lines are acquired separate from the imaging scans.
These are acquired after the dummy scans and before the imaging scans.
3.2.9 Slice timing
Typically, a multislice protocol (multiple slices per measurement) is used for BOLD EPI scans. Since each slice
is acquired at a different time, a “slice timing correction” must be applied to account for these differences in
acquisition time in relation to the stimulus. In the MOSAIC display format though, the timing of each slice is not
available, and only one time point is displayed for the entire volume. The acquisition time for each slice can be
extracted from the image header in syngo® software version VB15A. For VB13A and earlier software versions, this
time is not available in the header. The slices can be assumed to be distributed evenly in TR (Delay in TR).
Note: Take interleaved reordering when calculating slice timing, as described in Section 3.2.3.
3.2.10 Slice Time Correction
This means to account for slice timing differences relative to the stimulus. This is possible with syngo software
versions VB13A and later. See the BOLD Imaging Application Brochure, page 14, Covariates of no interest, column
5: Derivation of the activation pattern. It is necessary to model the offset in time while measuring the individual
slices. Prerequisites: Parameter “Ignore after transition = 0”, and “Model transition states” active.

10 fMRI User Guide
3.2.11 Spatial Filter specifications (conversion to mm)
From the BOLD Apps Brochure: Filter strength: A Gauss filter is used for image filtration. Smaller filter values effect
a stronger limitation of high signal values and therefore a stronger filtration.
Filter value Effect
2 weak
1.0 average
0.5 strong
From ICE programming manual:
<Label> "Filter Setting"
<Precision> 1
<LimitRange> {0.1 5.0}
// "Filter parameter for the 3D spatial filter. Please enter the value below (value must be > 0)."
// "Meaning: The filter window has reached zero for 'value'-times of the Nyquist frequency."
// "eff. resulting voxelsize is approx. = voxelsize * sqrt( 1+4/(value^2) )"
// "Note: smaller value = stronger filter."
<Default> 1.0
So, for 2 mm isotropic voxels, a fiter setting of 2 (weak) gives a resulting approximate voxel size of 2*sqrt( 1+4/
(1^2) ) = 2.8 mm isotropic. Average (1.0) gives 4.4 mm, strong (0.5) gives 8.2 mm.
3.2.12 Co-registration between data sets
There is no co-registration done in the Neuro3D taskcard. The recommendation is to use AutoAlign during data
measurement. This will automatically place all the data sets in the same reference frame.
3.3 fMRI Data analysis
For details on how to analyze the BOLD data, please refer to the BOLD Imaging Application brochure.