Biomed Imaging Interv J 2006; 2(4):e48
© 2006 Biomedical Imaging and
Evaluation of the quality of CT-like images obtained using a commercial flat panel detector system
JM Smyth1,*, MSc,
DG Sutton1, PhD,
JG Houston2 FRCR
1 Department of Medical Physics, Ninewells
Hospital and Medical School, Dundee, Scotland
2 Department of Radiology, Ninewells Hospital and Medical School,
Purpose: The development of flat panel detector
technology has resulted in renewed interest in the possibility of generating
CT-like images from rotational angiographic acquisitions. At least two
commercial products now use cone beam reconstruction software in conjunction with
flat panel detectors to produce such images. The purpose of the work presented
here is to report on image quality obtained from one such system in objective
and subjective terms and to compare it with the quality of images obtained from
a modern multi-detector CT scanner.
Method: The Image quality was assessed using a
CATPHAN 500 model and an AAPM CT Performance Phantom model. Image noise, CT
number accuracy, CT number consistency, Low Contrast Resolution, surface dose and Modulation Transfer Function were assessed for the flat panel
detector and compared with results obtained from a 4 slice CT scanner.
Results: As expected image quality obtained from the
CT scanner was much better than from the flat panel detector.� Low contrast
resolution was much worse and the surface dose was higher for the flat panel
detector than the CT scanner. There was an inaccuracy in CT number
determination and the noise was greater by a factor of two or three. Limiting
resolution was better on images from the CT scanner.
Conclusion: The poor low contrast resolution from
flat panel detector was expected given the expected resolution of �10
Hounsfield Units.� These systems should not be considered as diagnostic CT
scanners. However, the remaining performance figures indicate that the CT-like
images obtained from this type of equipment are of sufficient quality for at
least some clinical applications, such as detection of brain haemorrhages in
the vascular suite. � 2006 Biomedical Imaging and Intervention Journal. All
Keywords: CT-like images, flat panel detector, image quality
Rotational angiography is an image acquisition technique
which was designed to overcome some of the limitations of traditional
angiography introduced by the two dimensional depiction of complex three
dimensional structures. A major driving force behind the development of
rotational angiography has been the ability to apply CT-like algorithms for 3D
volumetric reconstructions . A consequence of the rendering approach is that
the resulting images lack the contrast resolution of true CT, being typically
able to resolve differences of some 100 Hounsfield Units (HU) compared to 1 HU
for conventional CT (Figure 1). Active matrix flat panel detectors have recently
been developed for fluoroscopic imaging  and are increasingly being
incorporated into angiographic equipment. Such detectors provide the efficient,
practically distortion free environment that is required for cone beam CT
reconstruction . Consequently, the development of flat panel detector
technology has resulted in renewed interest in the possibility of generating
CT-like images from rotational angiographic acquisitions. The potential
increase in contrast resolution to almost 10 HU may have considerable
implications during angiographic procedures. For example, in neuroradiology,
brain haemorrhages resulting from pathology or during a coiling process may be
visualised, and in abdominal radiology it may be possible to image vessels
without the introduction of a contrast agent (Figure 1). At least two major
manufacturers have products that utilise cone beam reconstruction software in
conjunction with flat panel detector to produce CT-like images from rotational
angiography acquisitions. There is very little published data on the utility of
these systems; one paper discusses the utility of CT-like images in
neuroendovacular procedures  and reports that the quality of the images is
sufficient for diagnosis.
Figure 1 Hounsfield unit resolution
(Delta HU) required for a range of clinical indications with
arrows showing minimum contrast resolution for rotational
angiography, DynaCT and conventional CT.
The ability to use axial 2D in an interventional radiology
suite rather than a CT scanner room has distinct advantages in patient
monitoring, access for procedural instruments and devices, supportive equipment
and staff familiarisation. Such advantages may offset the poorer image quality
achieved, particularly if a combination of CT-like images and standard 2D and
2D rotational techniques are employed. However, a better understanding of the
relative image quality differences between the CT-like images obtained using
rotating flat panel detector systems and those obtained in the CT suite is
essential for further progress in this area. The purpose of the work presented
here is to report on the image quality obtained from one such system in both
objective and subjective terms and to compare it with the quality of images
obtained from a modern multi-detector CT scanner.
The equipment used in this study, the Siemens Axiom Artis
dTA, is a ceiling mounted C-arm angiography system with an amorphous silicon
flat panel detector for use in interventional and diagnostic applications. In
addition to digital fluoroscopy, subtraction and non subtraction digital
acquisition, Axiom Artis dTA can perform rotational angiography (Dynavision)
with 3D reconstructions displayed on an imaging workstation (Figure 2). Siemens
Medical have developed specialised software (DynaCT) to allow reconstruction of
CT-like data sets with soft tissue resolution from rotational angiographic
acquisitions (Figure 3).
Figure 2 Example of renal subtraction
images obtained using 3D rotational angiography.
Figure 3 The same volume
as shown in Figure 2 but processed using DynaCT.
Images are acquired using a 30 cm x 38 cm amorphous silicon
detector with 2480 x 1920 matrix size (154 μm pixel pitch) and 14-bit
depth. The acquisitions are carried out using a partial (200�) rotation with the X-Ray tube moving
underneath the table top. There are three rotation times (5s, 10s and 20s),
which correspond to 133, 248 and 495 projection images at 1.5�, 0.8�
and 0.4� increments. The kV and mA are
selected using Automatic Exposure Control and depend on the detector dose
selected: 0.36 mGy or 1.2 mGy. The X-Ray radiation is pulsed; typical
pulse widths are 7.5ms or 11ms. The largest field size is the default although
some collimation is theoretically possible. The stated contrast resolution is
of the order of 10 HU. The source to detector distance is fixed at 118cm,
giving a 25cm field of view at centre of rotation in the default configuration.
This should be compared to a conventional CT scanner with scan fields of view
up to 50cm at the isocentre for body acquisitions.
To acquire volumetric data from the cone beam projections, a
modified Feldkamp reconstruction algorithm is utilised. The recommended
reconstruction kernel is based on a Shepp-Logan filter but there is some
suppression of high spatial frequencies and summation of several detector lines
to reduce noise and increase low contrast resolution. Other corrections are
applied to improve the images, such as measures to reduce the contribution from
scattered radiation (software scatter correction), application of compensation
for objects that do not fully fit into detector (truncation correction) and
balancing of pixel response to correct for ring correction artefacts. Grey
scale values are adjusted to an HU scale after the corrections have been
The images are displayed in 256 x 256 matrix with 8 bit
The multi-detector CT scanner used for comparison in this
study is a GE LightSpeed Plus 4 slice scanner. An evaluation report for this
scanner, including a technical summary, can be found on the UK NHS Purchasing
and Supplies Agency (PASA) website .
Materials and Methods
Image quality was assessed using a CATPHAN 500 model (The
Phantom Laboratory, Salem NY) and an AAPM CT Performance
Phantom model 76-410-4130. Both these phantoms have diameters of 20cm and
are similar in size to head phantoms (typically 16cm). Using larger, body sized
phantoms would result in loss of peripheral detail, as the field of view is
only 25cm at the centre of rotation (body phantoms typically have a 32cm
diameter). Figure 4 shows a 3D reconstruction of the CATPHAN generated
following a rotational acquisition.
Figure 4 A CATPHAN 3D reconstruction
processed using DynaCT.
The kV automatically selected by the AEC system was
approximately 70 kV for both phantoms. The mAs automatically selected by the
AEC system varied depending on the region of phantom being imaged and nominal
dose to the detector. It is recognised that the kV and mAs values clinically
used for head applications may vary to some extent from those selected for
Noise analysis and CT number evaluation for flat panel
detector images were performed on a Siemens Leonardo workstation using the
software tools provided. MTF measurements were performed using an IDL program
previously developed in-house for the analysis of CT images of a wire. DynaCT
acquisitions were obtained with phantoms positioned on the table top and offset
in the longitudinal direction so that centre of rotation coincided with centre
of the imaging module in question.
The same phantoms were used to assess image quality on the
CT scanner. An equivalent, or where possible, the same acquisition and image
parameters were used similar to the flat panel detector system. Images were
acquired in axial mode with 25cm field of view at the isocentre using a head
bow tie filter, and displayed at 25cm field of view. All images were
reconstructed using a 512 x 512 matrix and, unless otherwise stated, standard
The Axiom Artis dTA system had undergone extensive
acceptance and commissioning tests within six months of this study. An in-air
calibration was performed on the CT scanner prior to acquisition of the images
and routine image quality analysis is performed on a weekly basis.
I. Image Noise and CT Number of Water
Image noise and CT number of water were determined from
images of the CATPHAN CTP422 liquid bath module. Acquisitions were obtained at
low dose (0.36 μGy/frame) with 5s and 10s rotations and at high dose (1.20
μGy/frame) with a 20s rotation time. The kV and mA were under AEC control
and the field size was 30cm x 38cm at the flat panel detector (magnification
Raw data was processed at the workstation using the default
DynaCT InSpace reconstruction presets (Table 1). The volume data was displayed
on the workstation 3D card (Figure 5) and a multiplaner formatting (MPR) tool was
used to create axial images at specified image slice widths (Figure 6), as in
conventional CT. Axial images were analysed on the workstation using the
supplied measurement tools; a circular region of interest (approximately 1500
pixels) was drawn in centre of the image (Figure 7) and the area, mean pixel
value and standard deviation (in pixel value) for the region of interest (sROI) were displayed. The CT
number of water was taken to be the mean pixel value and the noise was as
Figure 5 DynaCT volume data displayed
as MPR images on Leonardo Workstation 3D card.
Figure 6 MPR tool used
to create images at specific slice widths from a coronal view.
Figure 7 Axial image of
CATPHAN Water module with ROI measurement tool.
Table 1 DynaCT InSpace
Percentage Noise =
where CTH2O and CTair are the CT
numbers of water and air respectively. A single image in centre of phantom was
analysed for each of the four acquisitions.
For conventional CT, the centre of the CATPHAN CTP422 liquid
bath module was placed at the scanner isocentre. Axial images were acquired and
analysed on the CT scanner console using the supplied measurement tools; a
circular region of interest (approximately same physical size) was drawn in
centre of the area, mean pixel value and standard deviation (in pixel value)
for the region of interest (sROI)
were displayed. The CT number of water was taken to be the mean pixel value and
the noise was as defined as above.
II. CT Number Consistency
To check CT consistency, a CATPHAN CTP401 sensitometry
module containing four materials of differing attenuation: air (75% N, 23.2% O,
1.3% Ar), LDPE (C2H4), Teflon (CF2) and acrylic
(C5H8O2), each of 1.2cm in diameter was
positioned symmetrically at 1.8cm from edge of the phantom. Acquisitions were
obtained at the low dose setting (0.36 mGy/frame)
with 5s rotation time. The kV and mA were under AEC control and the field size
was 30cm x 38 cm at the flat panel detector.
Axial images were generated, as described in the previous section,
and analysed using the supplied measurement tools. A circular region of
interest was drawn in centre of each material (Figure 8) and the area, mean pixel
value and standard deviation (in pixel value) for region of interest (sROI) were generated. The CT
number of each material was taken to be the mean pixel value. The final result
was obtained by averaging the data obtained from three adjacent axial images.
Figure 8 Axial image of CATPHAN sensitometry
module with ROI measurement tool. Note the radial streaks
characteristic of photon starvation.
For conventional CT, the centre of CATPHAN CTP401
sensitometry module was placed at the scanner isocentre. Axial images were
acquired and analysed on the CT scanner console using the supplied measurement
tools. A circular region of interest was drawn in centre of each material and
the area, mean pixel value and standard deviation (in pixel value) for region
of interest (sROI) were
generated. The CT number of each material was taken to be the mean pixel value.
III. Low Contrast Resolution
Low contrast resolution was assessed using a CATPHAN CTP515
low contrast module containing low contrast target discs arranged in three
groups with nominal contrast of 0.3%, 0.5% and 1.0% and decreasing diameters of
15mm, 9mm, 8mm, 7mm, 6mm, 5mm, 4mm, 3mm and 2mm. The acquisitions were taken at
low dose (0.36 mGy/frame) with 10s and
20s rotations and at high dose (1.20 mGy/frame)
using a 20s rotation time. The kV and mA were under AEC control and the field
size was 30 cm x 38 cm at the flat panel detector. The dose was measured on the
anterior surface of the phantom using a pencil ionisation chamber (Vertec PC-4P
Axial images were generated and displayed on the workstation
using the default window levels (Figure 9). The number of discernable discs in
each nominal contrast group were recorded by a single observer and
corresponding disc diameter identified.
Figure 9 Axial image of CATPHAN LCD
module generated using DynaCT.
For conventional CT, the centre of CATPHAN CTP515 low
contrast module was placed at the scanner isocentre. The dose was measured on
the anterior surface of the phantom using the same pencil ionisation chamber.
Axial images were displayed on the CT scanner console using default window
levels. The number of discernable discs in each nominal contrast group were
recorded by a single observer and corresponding disc diameter identified.
IV. Modulation Transfer Function (MTF)
MTF was determined using an AAPM CT Performance Phantom
model 76-410-4130 containing a stainless steel wire of 0.355 mm diameter and
15 cm length positioned 5.0 cm off centre in longitudinal (z-axis) direction. The
acquisitions were obtained at low dose (0.36 mGy/frame)
using a 5 s rotation time. As before, the kV and mA were under AEC control and
field size 30 cm x 38 cm at the detector surface. The axial images were generated
and transferred in DICOM format to a remote computer for analysis using
The software uses an estimated point spread function obtained from radially averaging a series of pixel value profiles across the image of the wire. The MTF is derived from the modulus of the Fourier Transform of this function and is expressed as the frequency in cycles per cm corresponding to 50% and 10% modulation.
In the case of conventional CT, the AAPM CT Performance
Phantom was positioned off centre so that the wire was within 1cm of the
scanner isocentre. Axial images were generated and transferred in DICOM format
to a remote computer for analysis using the in-house software described above.
Results & Discussion
I. Image Noise and CT Number of Water
The results are presented in Table 2 which also shows the CT
number and noise obtained from a GE LightSpeed Plus CT scanner using a) generic
exposure parameters at 80kV and b) standard brain protocol of 120kV, 240 mAs
and a 10mm slice width on the same phantom.
Table 2 Image noise and CT number of
water using standard reconstruction parameters
In conventional CT, the system is calibrated to give a CT
number of zero for water, which was the value obtained for both sets of
scanning parameters. The CT number from the DynaCT acquisition varied from -8
to -22. This must be interpreted within the context that the quoted resolution
is +/- 10 HU and given that the modality is designed to be used in an
interventional suite, cannot be considered to represent a significant error.
Theoretically, the image noise depends on the number of
photons and varies with the reciprocal of the square root of mA, time and image
(mAs * slice width)-1
This exact relationship may not hold if additional
corrections are applied in processing but noise will increase if mAs or slice
width are reduced, as observed in Table 2 for both DynaCT and conventional CT.
The noise is greater in DynaCT in all but the highest dose option, as might be
expected given the difference in the number of projections used for image
reconstruction. Nevertheless, at between 1-1.5% noise values are fit for this
II. CT Number Consistency
Three adjacent images were analysed and the average CT
number obtained for each of the test materials; Air, LDPE, Acryllic and Teflon
is presented in Table 3. In addition, results are given for a GE LightSpeed
Plus CT (4 slice) scanner using the same phantom with similar exposure
parameters (80 kV) and a more conventional potential of 120 kV.
Table 3 CT number consistency using
standard reconstruction parameters
Although there is no de facto right answer for the CT
number of the test materials (with the exception of water) the DynaCT �CT
number� for LDPE, Acryllic and Teflon is lower than the number obtained from
the CT scanner. Inspection of Table 2 shows the same is true in the case of
water. The DynaCT �CT� number for air is higher than that obtained from the CT
scanner at either kV. The CT number is related to linear attenuation
coefficient, which is a function of energy. The CT number of a material is
therefore not a constant and will depend on the incident X-Ray spectrum, which
in turn depends on the tube characteristics such as filtration and potential.
It is not unexpected, therefore that values for the materials are not the same
as for conventional CT scanner given the differences in CT X-Ray spectra
compared to fluoroscopy X-Ray spectra (Figure 10)  which is considerably
"softer" because of the reduced filtration.
Figure 10 Comparison of CT tube spectra
to fluoroscopic tube spectra. Fluoroscopic Spectrum 3mm Al,
70 kV. CT spectra 7 mm Al, 80 kV and 120 kV. The figure shows
the difference in quality between the three spectra resulting
from the difference in filtration and accelerating potential.
Each spectrum is normalised to its own maximum.
It is worth noting that the DynaCT image of Figure 8 shows
the radial streaking characteristic of photon starvation probably caused by
combination of high attenuation materials in the module and minimal number of
projections (133) obtained.
III. Low Contrast Resolution
The results are shown in Table 4 which also shows the low
contrast resolution obtained from a GE LightSpeed Plus CT scanner using the
standard brain protocol of 120 kV, 240 mAs and a 10mm slice width on the same
phantom. The results from the DynaCT system are, as one would expect,
demonstrably inferior. For example, the standard CT brain protocol at 120 kV is
capable of identifying a 5mm disc at 0.3% contrast with a surface dose of 6
mGy. The DynaCT system only manages to identify the 5mm disc at a contrast of
1% and requires a surface dose of at least 17 mGy. Increasing the dose does not
improve the low contrast resolution noticeably and the lowest dose DYNA option
does not even identify a 15mm disc at 1% contrast.
Table 4 Low contrast resolution using
standard reconstruction parameters
IV. Modulation Transfer Function
The results for MTF50% and MTF10% (line pairs/cm) are
presented in Table 5 which also shows typical MTF values for two algorithms
used in the reconstruction of images of the same phantom obtained with a GE
LightSpeed Plus CT scanner. As can be seen, the MTF for conventional CT is
slightly better for standard algorithms and considerably better for high
resolution edge enhancement algorithms. The 10% MTF for the standard CT
algorithm is 5.5 cm-1 whereas for the DynaCT images it ranges from
4.8 cm-1 to 4.3 cm-1. The apparent dependence of MTF on
mAs is due to uncertainty in the measurement method. Images with a low signal
to noise ratio will produce MTF curves with more statistical variation and
hence will exhibit some difference in MTF values, especially at lower
Table 5 Modulation Transfer Function
using standard reconstruction parameters
Clearly DynaCT is inferior to CT in imaging terms and should
not be thought of as bringing diagnostic CT scanning capabilities to the
interventional suite. Overall, DynaCT offers inferior image quality compared to
conventional CT using same phantoms and typical exposure parameters. The low
contrast resolution is significantly worse. This is not surprising given the
differences in equipment characteristics (matrix flat panel versus ceramic
solid state detectors), the reduction in the number of projections acquired and
the differing reconstruction techniques and corrections. The surface dose is
higher than in conventional CT for lower contrast.
However, although noise and CT number accuracy are inferior
to conventional CT, they are probably not significant, given the intended use
of the technology. For example, the noise levels of 1-1.5% are lower than those
routinely found in abdominal or high resolution head CT investigations .
Although subject to some error, CT numbers are of the right order. High
contrast spatial resolution is worse but not significant compared to
conventional CT. These latter characteristics render DynaCT suitable for at
least some clinical applications proposed, such as detection of brain
haemorrhages or identification of abdominal pathology (such as assessment of
the outcome of tumour embolisation immediately following the procedure) where
low contrast visualisation is not a dominant factor. The advantage is that
these 3D imaging procedures, which do not require the exceptional low contrast
discrimination provided by conventional CT scanners, can be performed in the
interventional suite when required and will remove the necessity for an �intra
procedure� CT scan. Thus if DynaCT (or its equivalents) is employed as an
adjunct to the imaging acquisition presently used in the vascular suite; it has
the potential and capability, at least in imaging terms, to be a valuable tool
in the interventional environment.
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|Received 27 July 2006; received in revised form 18 October 2006;
accepted 23 November 2006
Correspondence: Medical Physics Department, Acute
Services Division, Ninewells Hospital and Medical School,
Dundee DD1 9SY, Scotland. Tel.: +44 1382 632367; Fax: +44
1382 640177; E-mail: firstname.lastname@example.org
Please cite as: Smyth JM, Sutton DG, Houston
Evaluation of the quality of CT-like images obtained using a commercial flat panel detector system, Biomed Imaging Interv J 2006; 2(4):e48
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