Transcript Analysis of the stability of the Varian OBI(R) system flat

Analysis of the stability of the Varian OBI® system flat panel detector
Ariel Jefferson, Dandan Zheng, Jun Lu, Jeffrey Williamson
Department of Biomedical Engineering and Department of Radiation Oncology, Virginia Commonwealth University, Richmond, VA, USA
Purpose
Data Analysis and Results
Methods and Materials
CT Number Comparison
1000
with On-Board Imager
Background Information
As the use of LINAC- integrated
CBCT imaging systems becomes
more prevalent in image guided
radiation therapy (IGRT), it
demands sufficient attention to
quality assurance (QA) of the
systems to ensure optimal
performance. The system
investigated here has an FPD
with a 2048x1536 grid of digital
channels to detect transmitted xray signals. The channels
produce variations that
necessitate calibration.
Catphan 600 phantom
Standard Image Acquisition
•Signals from the channels are
read out in dual gain mode which
employs a high gain readout and
a low gain readout.
•Acquire one flood-field, one
normalization, and two dark-field
images.
•From these images, generate
gain maps, offset maps, and
defect maps using manufacturersupplied software
•As a control, one CBCT image of
a Catphan phantom was
acquired. A CBCT image is a 3D
volumetric representation of the
object.
-1500
-1000
-500
600
8282008
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8292008
200
9022008
0
9032008
-200
0
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1000
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9102008
-400
9162008
-600
9222008
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Dead Pixel Fluctuations Over Time
Offset Value Fluctuations
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7000
Raw Image Intensity
40
35
6000
5000
4000
High Gain
Low Gain
3000
2000
30
25
High Gain
20
15
10
Low Gain
5
0
1000
0
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Date
Varian Trilogy® Linear
Accelerator
Nominal HU
•Statistical analyses of the
number of defective pixels and
the pixel to pixel offset values
were performed in Excel.
Offset Value
Hardware
•Varian Trilogy® OBI
•Normalization Phantom
•Catphan 600 phantom
Software
•Varian Software
•Matlab
•Excel
•ImageJ
Number of Dead Pixels
To investigate the stability of the
flat panel detector (FPD) in a
widely used cone beam CT
(CBCT) system in terms of gain,
offset, and pixel fluctuations over
time, and to assess their effects
on image quality and establish
the minimum required frequency
of FPD calibration.
800
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Date
•In the gain map analysis,
histograms of the results
were obtained, and all of
them exhibit a Gaussian
distribution around 1.
 HG (i) 
 LG(i) 


 HG(control ) 
 LG(control ) 


Discussion
•The FPD electrical components
are subject to fluctuations in
behavior. Such slight fluctuations
did not affect the CBCT image
reconstruction in this study.
 Future work can be performed
to establish an absolute minimum
frequency of FPD calibration.
Conclusion
•Compare the gray
values (Hounsfield
Units) of known
materials to
analyze CT
reconstruction.
•For the studied CBCT system, a
monthly calibration frequency is
sufficient to maintain a 98.1%
level of stability indicated by the
fluctuations in defective pixels.
References
Schmidgunst C, Ritter D, Lang E. “Calibration Model of a dual gain flat panel
detector for 2D and 3D x-ray imaging.” Journal of Medical Physics, Volume
34, Issue 9, pp. 3649-64, September 2007
Example of a reconstructed
CBCT slice of the Catphan
Matsinos E. “Current status of the CBCT project at Varian Medical Systems.”
Medical Imaging 2005: Physics of Medical Imaging, edited by Michael J.
Flynn, Proceedings of SPIE, Volume 5745, pp. 340-51