Download Automated Measurement of Scanner Stability for Functional Brain

yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Brain damage wikipedia, lookup

Neuropsychopharmacology wikipedia, lookup

History of neuroimaging wikipedia, lookup

Automated Measurement of Scanner Stability for Functional Brain Imaging
James J. Pekar, Joseph S. Gillen, Terri L. Brawner, and Peter C.M. van Zijl
F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
& Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
The purpose of this study was to develop an automated
version of Weisskoff's method [R.M. Weisskoff, "Simple
measurement of scanner stability for functional NMR
imaging of activation in the brain," Magn. Reson. Med.
1996; 33:643-645] for assessing the temporal stability of an
MRI scanner for functional brain imaging.
Data were acquired from a CuSO4-doped standard
phantom in a Philips Gyroscan NT PT-6000 scanner using
the standard receive-only quadrature headcoil combined
with body-coil excitation. Single-shot gradient-echo Echo
Planar Imaging was used with TE/TR = 50/3000 msec.
Slice thickness was 5 mm; matrix size was 64x64; nominal
resolution was 3.75 mm. After five "dummy scans,"
allowing equilibrium to be reached, 300 images were
acquired over 15 minutes.
Typical performance of the erosion-based method for
automated generation of regions-of-interest is shown in
figure 1. The corresponding stability data are shown in
figure 2, which plots relative deviation vs. region of interest
diameter. Relative deviation of less than 0.05 percent over
fifteen minutes is shown for the largest region-of-interest.
Figure 1. Demonstration of automatic generation of regions of interest.
Top left corner: Image. Next item to right: Starting region of interest,
produced from thresholding and erosion of original image. Remaining
items, from left to right, top to bottom, show regions of interest resulting
from sequential erosion
Relative Deviation, %
Functional MR imaging of brain activation using BOLD
contrast requires a stable scanner. Weisskoff introduced a
robust measure of scanner stability which relies upon the
computed relative deviation over time of MR signal
averaged over different-sized regions of interest (1). A
log-log plot is made of this deviation vs. the "diameter"
(square root of number of pixels) of the region of interest.
In the ideal case, all deviation over time would be due to
Johnson noise, and the plot would be a downwards sloping
straight line reflecting the √N sensitivity advantage of
averaging over voxels. As no scanner is perfectly stable,
the computed data points will lie above this line, and their
asymptote will reveal the limit of scanner stability.
Weisskoff’s method is extended here by use of the
erosion operator, from mathematical morphology, to
produce automatically the required regions of interest,
allowing the stability measurement process to be fully
automated. The erosion operator was used both to create the
starting, largest, region of interest, and in producing the
smaller regions: First, a 10% threshold, followed by
erosion (by a seven-by-seven pseudodircle) were used to
generate a large starting region-of-interest. Then,
sequential erosion by a three-by-three square (also known,
in morphology, as the 8-connected set, or N8) was used to
progressively "shrink" the region of interest until it
vanished, at which point a "remembered" single pixel from
the last non-vanishing region was used as the single-pixel
region of interest.
ROI Diameter, pixels
Figure 2. Stability plot. Relative deviation, over a period of 15 minutes,
versus region of interest "diameter" (square root of the number of
pixels); produced using automatic generation of regions of interest.
Use of the erosion operator (2) allows for automatic
generation of the different-sized regions of interest needed
for assessment of scanner stability using the method of
Weiskoff (1). We have found this automatic calculation of
scanner stability to be a convenient daily check of scanner
1. Weisskoff RM. Magn. Reson. Med. 1996; 33:643-645.
2. Serra, J. Image Analysis and Mathematical Morphology.
Academic Press, 1984.
Acknowledgments Work performed at the F.M. Kirby
Research Center for Functional Brain Imaging at Kennedy
Krieger Institute.