BOLD effects of interest are small, so temporal stability during
functional acquisition is important. In order to accurately measure such
small signal changes, an MR system must have intrinsic image time
series fluctuation levels much lower than these expected signal changes.
Quality checks allow you to assess if your data are worth being
analyzed.
Acquisition (artifacts)
SNR - signal to noise - single image (contrast to noise, dropout/susceptibility; gray/white matter contrast in structurals)
SNR - temporal (e.g., maps of mean / std. deviation across time)
ghosting - image wrap-around artifact*
image intensity - high enough to avoid information loss? (e.g., >1000)
distortions - spatial distortions in acquisition
Motion artifacts mainly propagate in the phase-encode direction. This is
due to movement of the spins between 2 excitations or between
phase-encoding and signal reading: in the first case, the spins will not
be recorded at the same position between excitations, in the second
case, their phase-encoding will not be correct. As a result, the
phase-encoding of these voxels is corrupted and this will be responsible
for artifacts in the phase-encode direction.
On the other hand,
signal sampling and spatial-encoding in the frequency-encode direction
are done so fast that physiological motion will only produce a small
amount of spatial blurring in that direction.
Spikes - gradient artifacts and bad images *
drift - large signal drift over time (look at FFT or timeseries)
periodic noise - low-frequency noise artifacts
When the movements are periodical (cardiac beats, arterial or CSF
pulsations, respiration), they can produce ghost images, propagated in
the phase-encode direction, even outside the anatomic limits. The
intensity of these ghost images becomes more extreme with the intensity
of the moving structure and with the amplitude of movement. These ghost
images can show up as an increase or decrease of the true image signal.
The spacing between ghost images varies with the direction of the
movement, its amplitude and its periodicity relative to the
phase-sampling interval (TR).
streaks/striping in images (RF room leaks)
Processing
orientation (reconstruction/header problems)
skull stripping or segmentation failures (missing brain)
coregistration (anatomical to functional overlap)
normalization (warping was ok? bad alignment/distortion?)
movement estimates (reasonable? too much movement?)
Modeling/statistics
colinearity and predictor variance in model
mask (which voxels are analyzed?)
image registration (consistent across all images in analysis?)
contrast scaling (consistent across all images?)
indicators of task-correlated artifacts: global shift, large std across contrast
outliers (very unusual images)
Reference: http://wagerlab.colorado.edu/wiki/
http://www.imaios.com/en/e-Courses/e-MRI/Image-quality-and-artifacts/image-quality
No comments:
Post a Comment