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Quality control of CT image using American College of Radiology (ACR)

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DOI: 10.1016/j.ejrnm.2016.08.016

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 The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx

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Original Article

Quality control of CT image using American College

of Radiology (ACR) phantom
Z. Mansour a, A. Mokhtar a, A. Sarhan b, M.T. Ahmed b,⇑, T. El-Diasty a
a
Radiology Department, Urology and Nephrology Center, Mansoura University, Mansoura, Egypt
b
Physics Department, Faculty of Science, Mansoura University, Mansoura, Egypt

a r t i c l e i n f o a b s t r a c t

Article history: Objective: To study image quality of CT scanner using the American College of Radiology
Received 19 June 2016 (ACR) phantom.
Accepted 21 August 2016 Material and methods: A multidetector CT scanner was used to measure parameters of
Available online xxxx
image quality using ACR phantom. The phantom included four modules to measure these
parameters. We obtained CT image for each module to measure these parameters for the
Keywords: brain protocol.
CT
Results: The acceptable levels of image quality were obtained for the positioning, CT num-
ACR phantom
Image quality
ber accuracy, slice thickness, low contrast resolution, uniformity and high contrast resolu-
tion tests that represent the parameters of image quality. In positioning test, the three BBs
were visible. In CT number accuracy, the CT number of three materials was in the range of
tolerance values unlike the bone value which was 846 HU. In low contrast resolution test
the smallest contrast groups were seen. In High contrast resolution test the 5 lp/cm was
visible. All these tests of image quality were accepted because they were within the toler-
ance values, so the quality of Philips CT scanner was improved. Ring artifact was indicated
also, which is a type of scanner performance errors.
Conclusions: Image quality tests are very important tests in acceptance of any CT scanner
after installation and maintenance to approve that the image parameters are acceptable by
using ACR phantom.
Ó 2016 The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by
Elsevier. This is an open access article under the CC BY-NC-ND license (http://creativecom-
mons.org/licenses/by-nc-nd/4.0/).

1. Introduction parameters that control exposure of the patient and the

display of the images and also regular checking of scanner
Annual scans of computed tomography (CT) have been performance with measurement of physical image param-
increased rapidly from 2 to 72 millions from 1980 to eters as part of program of quality assurance [5] for achiev-
2007, approximately [1–4]. Good imaging performance ing accredited status for CT through the American College
indicates that image quality should be sufficient to meet of Radiology (ACR) Accreditation Program. This program
the clinical requirement for the examination. At the same has the most powerful radiation safety standards and
time maintaining the dose to the lowest level is reasonably demonstrates the fundamental details that allow us to con-
practicable. There must be careful selection of technical duct fitly designed and achieved studies using optimized
equipment [6,7]. To evaluate image quality the ACR-CT
accreditation program was used. Our objective was to
Peer review under responsibility of The Egyptian Society of Radiology and
increase image quality using the (ACR) accreditation phan-
Nuclear Medicine.
⇑ Corresponding author. tom (Gammex 464).

http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
0378-603X/Ó 2016 The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
2 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx

2. Materials Slice thickness, Low contrast resolution, High contrast

(spatial) resolution, CT number uniformity and Image noise
2.1. CT scanner [13–15]. Module 1 is used for evaluating phantom posi-
tioning and it has cylindrical rods for assessing the CT
Multidetector CT scanner (Brilliance, Philips Medical number of different materials (water, polyethylene, acrylic,
System, Eindhoven, the Netherlands). bone, and air). It is also used for measuring slice thickness.
Module 2 tests low-contrast resolution and it has different
sized sets of cylindrical rods whose CT number differs from
2.2. American College of Radiology (ACR) phantom the background material by 6 HU. Module 3 is used to
measure image uniformity. Average CT numbers from
The ACR CT accreditation phantom consists of four peripheral regions of interest (ROIs) are compared with
independent parts which can measure the required image the average CT number from ROI at the center. Module 4
quality parameters [8,9]. tests high contrast resolution with eight different spatial
It is a solid phantom as illustrated in Fig. 1 (a) and is frequency bar patterns. Fig. 2 (a–d) illustrates the cross
constructed originally from a water equivalent material. sections of the four modules of the ACR phantom [16].
It is made of solid water, making this phantom a physically
stable device that provides reproducible results over time 3. Methods
[10]. Each module is 4 cm in depth and 20 cm in diameter
[11]. There are outer alignment markings scribed and We scanned seven images of ACR phantom for the brain
painted white to reflect alignment lights on each module protocol. We admitted during the period from March to
for allowing centering of the phantom [12]. The ACR CT June 2016 in the Radiology Department, Urology and
accreditation phantom has been designed to examine a Nephrology Center, Mansoura University, Egypt.
wide range of scanner parameters as shown in Fig. 1(b).
These include Positioning accuracy, CT number accuracy,
3.1. Scanning instructions

The parameters that are used in all the following tests,

were from Instruction Manual for the ACR CT Accreditation
Phantom.

3.1.1. Phantom and scanner alignment

The phantom was aligned in the coronal, sagittal, and
axial planes. We focused on the table at this point and
noted the table location, as all scans acquired in reference
to this location. While maintaining careful alignment, we
had ensured that the phantom will not move [17].

3.1.2. The Gammex 464 phantom (ACR) scanning with our

facilities
We used the axial brain protocol in this work.

3.2. Positioning test

The table was moved so that the alignment light was

carefully centered over module 1. The position of the cen-
ter of module 1, reference location (landmark location) was
recorded. We used the scan parameters listed for position-
ing test in axial brain as shown in Table 1.
On data sheet we recorded the visibility of four BBs.
Then we moved the table to center the alignment light
over module 4 and repeated this for module 4.

3.3. Determination of CT number calibration and slice

thickness

Fig. 1. (a) Photograph of correctly aligned ACR phantom and centering of For CT number calibration, the alignment light was cen-
the phantom in the axial (z-axis, cranial/caudal), coronal (y-axis, ante- tered again over module 1. We used the same scan param-
rior/posterior), and sagittal (x-axis, left/right) directions. (b) Four modules eters that are used in positioning test with varying
of ACR phantom indicating the scanner parameters. Module 1 measures
alignment, CT number accuracy and slice thickness, Module 2 measures
following parameters SFOV = 220 mm, Ww = 400 HU,
low contrast resolution, module 3 measures uniformity, noise and ssp. Wl = 0 HU, thickness = 5 mm and scan time = 1.5 m. Acicu-
and Module 4 measures high contrast resolution. lar region of interest (ROI) of approximately 200 mm2

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx 3

Fig. 2. (a) Module 1 shows five cylindrical rods: Water, bone, polyethylene, air, and acrylic. (b) Module 2 shows different sized cylindrical rods. (c) Module 3
consists of tissue equivalent materials. (d) Module 4 shows eight different spatial frequency bar patterns.

Table 1
Scan parameters used in alignment of ACR phantom in axial brain protocol.

Phantom ACR GAMMEX 438 # image 1 Scanner BR64

KV 120 Rec. Algor. Std (UB) Label Alignment
MA 200 Protocol Head Axial Start 0&120
SFOV 220 mm W/level 0 End 0&120
ROI size NA Resolution High Length 3.85
W/width 1000 Collimation 2  0.625 Thickness 1.25
FOV 250 Tilt 0 Rotation time .5

within each cylinder was placed, and on the data sheet, the An image at this location was acquired. We viewed the
mean CT numbers for each material were recorded [18]. image located at the center of module 2, and noted that
For slice thickness determination, we used sets of slice there were four cylinders for each of following diameters:
thickness to measure their thickness. We used slice thick- 2, 3, 4, 5, and 6 mm.
ness = 4 mm and filmed this image. To determine this We determined which all four cylinders were visual-
thickness, we counted the number of wires seen in the ized. The diameters of these cylinders were recorded on
top or the bottom and divided by two. This step was the data sheet. We were able to see the 6-mm rod.
repeated for the following slice thicknesses 1.3, 3.8,
2.5 mm. We recorded the measured slice thickness on data
sheet. 3.5. Noise determination

The same scan parameters listed for module 2 were

3.4. Determination of low contrast resolution used. A circular ROI of approximately 100 mm was placed
over the large (25-mm diameter) cylinder and next to the
The table was moved to center the light over module 2 large cylinder. ROI inside 25 mm rod was (A) and outside
(40 mm superior to the location of the center of module 1). the 25 mm rod was (B). We recorded the mean CT number
We used the following parameters: ROI = 100 mm, for each ROI, calculated the difference, and recorded the
Ww = 100 HU, Wl = 100 HU and collimation = 5  4 mm. Standard Deviation (SD) from the ROI outside the 25 mm

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
4 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx

rod. This image was filmed with the two ROIs. All four rods values as indicated in Table 2 and Fig. 4. Then we com-
(of a given diameter) must be seen. We used the following pared the actual and the measured CT numbers of these
formula for measuring the value of contrast to noise ratio. materials in this protocol as shown in Fig. 5. All these
CNR = |A B|/SD [16,17]. materials were nearly the same CT number of the actual
values except bone.
3.6. Uniformity and plane distance accuracy test
4.1.3. Slice thickness determination
The table was moved to center the light over module 3, Table 3 indicates the measured thickness and indicates
and we used ROI = 400 mm, Ww = 100 HU, Wl = 0, thick- that the tests of slice thickness determination were
ness = 5 mm, and collimation = 2  0.625 mm for this test. accepted for all the selected slice thicknesses. In Fig. 6 slice
The image at this location was filmed, and we placed an thickness equaled 4.
ROI of approximately 400 mm2 at the center of the image
(A) and the four edge positions. We recorded the mean
4.2. Module 2: Low contrast resolution measurements of ACR
CT numbers for all five ROIs for our records, then recorded
axial brain
the standard deviation of the center ROI. The CT numbers
for all five ROIs must be within ±5 HU of the center ROI
For module 2, we enabled to see group 25 in this test
mean value. Finally we calculated and recorded the unifor-
which indicated the smallest contrast group, and this
mity value (center mean CT number – edge mean) on the
data sheet [17].

3.7. High contrast (spatial) resolution

We adjusted the table to center the light over module 4.

We used Wl = 1100 HU, Ww = HU, and ROI = 4002 mm as
well as we noted the eight bar patterns. Carefully we
viewed the image with the room light lowered and deter-
mined the highest spatial frequency for which the bars and
spaces were clearly visualized [9].
On the data sheet we recorded the highest spatial fre-
quency that could be visualized and filmed this image.
The 4-lp/cm bar pattern was the easiest pattern to resolve
and appeared to have the widest spaces and widest bars.
The 12-lp/cm bar pattern was the hardest one to be
resolved.

3.8. Data analysis

The obtained image quality parameters were compared

with the tolerance values of ACR. Analysis of CT images
showed that the parameters of image quality were within
ACR guidelines for the scanned protocol.

4. Results

The following results of determining the parameters of

image quality were obtained using axial brain protocol.

4.1. Module 1

4.1.1. Positioning and CT number calibration of ACR phantom

in axial brain protocol
For module 1 and for module 4 we found that three BBs
and central lines were visible as shown in Fig. 3(a & b) and
this meant that the test was accepted.

4.1.2. CT number accuracy

For module 1, we found that the tests of the water, poly-
Fig. 3. (a) Alignment of ACR phantom in axial brain protocol for module 1
ethylene, and Acrylic were accepted because they did not showed that three BBs were visible, so the test was accepted. (b)
exceed the tolerance value, but the bone value was not Alignment of ACR phantom in axial brain protocol for module 4 showed
accepted which was 846 HU that is out of the tolerance that three BBs were visible also, so the test was passed.

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx 5

Table 2
The measured CT numbers of different materials in ACR axial brain.

Materials Actual Measured CT number (HU) SD (HU) (Max-Min) value Results

Air 1000 998 2.9 970 to 1005 Pass
Acrylic 120 124 3.1 135 to 110 Pass
Bone 900 846 5.4 970 to 850 Fail
Polyethylene 95 91 3 84 to 107 Pass
Water 0 0 3.4 7 to 7 Pass

4.3. Noise determination (module 3)

Module 3 is shown in Fig. 8, and the value of CT number

outside of phantom (B) equaled (91) HU and inside the
phantom equaled (98) HU. The difference equaled (7) HU.
The SD outside the phantom equaled (3.7) HU. The CNR
equaled (1.8), so the noise determination test was accepted
because the pass criteria CNR > 1 of the brain protocol.

4.4. Uniformity determination (module 3)

In module 3, the distance between two BBs = 99.9 mm

as shown in Fig. 8. This figure indicated that the measured
values of CT numbers of the top, bottom, left and right
were the same (0) HU except the value of the center which
was (3) HU.
The SD in center, top, right, bottom and left were 3.7,
Fig. 4. The measured CT numbers of different materials in ACR axial brain 3.4, 3.1, 3.4 and 3.3 (HU). The CT numbers in these five
showing SD selected ROI. All of these materials passed the test except
positions were within the tolerance value (±5 HU), so the
bone.
test of uniformity was accepted.

1000 4.5. High contrast resolution (HCR) for ACR axial brain

500 For module 4, Fig. 9 shows the obtained image of this

module. In this figure the group numbers 1 and 2 which
0
actual correspond to 4 and 5 lines per cm were clearly visible.
-500 measured This indicated the acceptance of this test. Finally, since
passing all of the previous tests of the brain using the
-1000 ACR phantom, the test of image quality was accepted.

-1500
5. Discussion
Fig. 5. Diagram illustrated the measured and actual CT numbers of the
different materials in ACR axial scan. All these materials are nearly the The provided figures indicated acceptable levels of
same CT number except bone. image quality, as well as a type of image artifacts (ring arti-
fact) and scanner performance errors, so biomedical engi-
neer was required to calibrate the detectors. For module
means that the test was accepted as shown in Fig. 7. It can
1, the test of alignments was accepted because the three
be concluded from Fig. 7 finding of ring artifacts, and it was
BBs that were visible were within the tolerance value.
due to the fact that one of the detectors was out of calibra-
The test of slice thickness determination was accepted
tion on this scanner; the detector gave a consistently erro-
also, because for slice thickness 1.3 mm, the number of
neous reading at each angular position, resulting in a
wires seen in the top or the bottom of the image and
circular artifact, so medical engineer was required [19].
divided by two, equaled (2). For 2.5 mm, the number of

Table 3
All the choosing thicknesses passed the test.

Thickness set No. of wires seen in top or bottom Thickness measured (mm) Tolerance value (mm) Results
1.3 2 1.0 ±1.5 Pass
2.5 4 2 Pass
3.8 7 3.5 Pass
4 8 4 Pass

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
6 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx

Fig. 8. Module 3 in ACR axial brain protocol showing that the CT numbers
Fig. 6. Slice thickness determination in ACR axial brain equaled the
in left, right, top, bottom and center are not exceeded the tolerance value
number of wires seen in the top or the bottom divided by two.
as the same time they are nearly the same values and BBs dis-
tance = 99.9 mm, but there are ring artifacts.

Fig. 7. Module 2 indicating low contrast group in ACR axial. There are Fig. 9. Module 4 in ACR axial brain protocol indicating eight different
four cylinders with 6 mm diameter. There is ring artifact. spatial frequency bar patterns. The visibility of 4 lp/cm and 5 lp/cm was
easy while 6,7,8,9,10,12 lp/cm were harder.

wires that were seen was 4. For 3.8 and 4 mm the numbers
of wires seen were 7 and 8. All the previous slice thick- 6 mm. The 6 mm cylinder was also seen, and the four cylin-
nesses that were selected were within tolerance value ders of it were visible, so the test was passed. This result is
(±1.5 mm). Our results are in agreement with those of Hob- in agreement with that of Nookala et al. [20].
son et al. The test of CT number accuracy was accepted For module 3 the uniformity test was also accepted,
also, because the measured CT number of polyethylene, because the measured values of the mean CT numbers of
acrylic, water and Air was within the range of the tolerance all four edges were (0) HU that were ±5 HU of the mean
values and they are in agreement with those of McCul- value of the center where the ±5 HU is the tolerance value.
lough et al. The bone value was not accepted, because it In module 4, the high contrast resolution test was
was out of the range of the tolerance values. It is in dis- accepted, since the tolerance values of the brain protocol
agreement with McCullough et al. for this test were 5 lp/cm and the 5 lp/cm which were vis-
We obtained this result of the bone value, because the ible. The result of uniformity and high contrast resolution
number of applied protocols was limited [9,10,19]. test is in agreement with that of Nookala et al. also [20].
For module 2, we know that this module has different
sized sets of cylindrical rods. We must see the smallest 6. Conclusion
low contrast group. The low contrast resolution test was
accepted, because we had seen the large cylinders To the best of our knowledge, this is the first study
(25 mm) that were necessary to be seen. The tolerance is carried out in Egypt.

Please cite this article in press as: Mansour Z et al. Quality control of CT image using American College of Radiology (ACR) phantom. Egypt J
Radiol Nucl Med (2016), http://dx.doi.org/10.1016/j.ejrnm.2016.08.016
 Z. Mansour et al. / The Egyptian Journal of Radiology and Nuclear Medicine xxx (2016) xxx–xxx 7

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