Key words
cardiac CT - iterative reconstruction - image quality - CT angiography - dose - iDose
Introduction
Cardiac computed tomography angiography (CCTA) enables reliable noninvasive examination
of the coronary arteries. Improvements in scanner technology since the 1990 s have
resulted in excellent temporal and spatial resolution with adequate visualization
of up to 97 % of coronary segments [1]
[2]. Coronary artery disease (CAD) can now be excluded by CCTA with a high negative
predictive value, thus helping to avoid unnecessary invasive angiography [3]
[4]. CCTA initially required radiation doses of up to 30 mSv due to retrospective ECG
gating combined with a very low pitch and the challenge of visualizing small vessels
[5]. Therefore, radiation exposure of CCTA has become a major concern in clinical practice
[6], and increasing awareness developed among the medical community. Many innovations
regarding radiation protection in CCTA including a tailored approach concerning tube
potential (low kV techniques) [7], ECG-based tube current modulation [8], and prospectively ECG-triggered image acquisition (“step-and-shoot”) have been
consecutively introduced. Using the “step-and-shoot” technique, mean radiation doses
of less than 5 mSv are achievable [9]
[10]
[11]. However, image quality remains an essential parameter for all low-dose examinations
as accurate visualization of the coronary tree is critical for CCTA.
Filtered back-projection (FBP) has been the preferred method of CT image reconstruction
since the 1970 s due to its fast and robust results [12]. Recently, CT reconstruction techniques, which are based on iterative reconstruction
(IR) algorithms, have become available for clinical CT. IR techniques use correction
loops to progressively refine image data and to separate image information from noise.
They offer a potential radiation dose reduction while maintaining high image quality
[13]
[14]
[15]. With early IR algorithms, effective noise reduction could be achieved by processing
data in image space similar to adaptive postprocessing filters [16]
[17]
[18]. Advanced IR systems also involve the raw data space and are even more powerful
with respect to reducing and preventing artifacts by integrating anatomy-based model
calculations.
This study was done to investigate the effects of an advanced 4th generation IR technique
on subjective and objective image quality (IQ) in low-dose cardiac CT angiography
(CCTA).
Materials and Methods
Patients
In this retrospective study we analyzed 30 contrast-enhanced prospectively ECG-triggered
CCTA examinations in 30 consecutive patients performed in a dose-optimized “step-and-shoot”
scan protocol between July and August 2011. Study patients (15 female, 15 male; mean
age: 61.3 ± 12.9 years) were all referred for CCTA from the department of cardiology.
The mean BMI was 25.4 ± 4.6. Indications for CCTA were high or intermediate pretest
probability for CAD (n = 17), known CAD with clinical aggravation (no evidence of
acute myocardial infarction) (n = 11), typical or atypical chest pain (n = 4), and
evaluation of bypass grafts (n = 3). A heart rate of 60 bpm or lower and a sinus rhythm
were targeted. If necessary, the patient’s heart rate was controlled with intravenous
(i. v.) beta-blocker (metoprolol 5 mg, Beloc® AstraZeneca, Wedel, Germany) immediately before the scan. Patients with an irregular
rhythm or heart rate higher than 70 bpm were excluded from “step-and-shoot” mode scanning
and were not included in the study. All patients received nitroglycerine (Nitrolingual
akut® 0.4 mg, Pohl-Boskamp, Hohenlockstedt, Germany) sublingually prior to CCTA.
MDCT scan protocol
CCTA was performed on a 256-row CT scanner (Brilliance iCT, Philips, Best, Netherlands).
The imaging protocol included anterior-posterior scout images and a non-contrast scan
to assess the coronary calcium score if clinically indicated. CCTA was obtained after
the administration of contrast agent (iomeprol, Imeron 350™, Bracco Imaging Group,
Italy). The amount of contrast and the flow rate were adapted to body weight in accordance
with [Table 1]. Injection of contrast was followed by a 40 ml saline flush at the same flow rate.
The start time of CCTA data acquisition was determined by a computer-assisted bolus
tracking program with a trigger threshold of 120 HU in the descending aorta; CT data
acquisition was started 12 s after triggering. The scan parameters included a 128 × 0.625 mm
collimation, gantry rotation time of 270 ms, tube potential of 100 – 120 kV, and a
tube load of between 100 and 200 electrical mAs. The tube potential and tube load
were selected according to the patient’s chest size ([Table 2]). The z-axis field of view extended from the carina or pulmonary artery segment
down to the diaphragm for native CCTA. In patients with coronary artery bypass graft
surgery, the z-coverage was extended. ECG-triggered image acquisition started at 78 %
of the RR interval. Axial images were reconstructed with a slice thickness of 0.6 mm
at a reconstruction increment of 0.5 mm.
Table 1
The volume and flow rate of the contrast medium was adapted to the body weight of
the patients.
Tab. 1 Volumen und Flussrate des Kontrastmittels wurde an das Körpergewicht des Patienten
angepasst, um eine konstante Kontrastierung zu erreichen.
|
body weight [kg]
|
contrast volume [ml]
|
flow rate [ml/s]
|
number of patients
|
|
< 90
|
70
|
5
|
23
|
|
90 to 100
|
80
|
5.5
|
5
|
|
100 to 110
|
90
|
6
|
2
|
Table 2
Mean values ± standard deviation for dose-related parameters in the patients of the
study group.
Tab. 2 Mittelwerte ± Standardabweichung der dosisrelevanten Parameter der Studienpatienten.
|
tube potential 120 kVp, n
|
5
|
|
tube potential 100 kVp, n
|
25
|
|
tube current time product, mean ± SD [mAs]
|
172 ± 39
|
|
CTDIvol, mean ± SD [mGy]
|
9.8 ± 3.8
|
|
dose length product (DLP), mean ± SD [mGy∙cm]
|
124 ± 46
|
|
scan length, mean ± SD [cm]
|
12.7 ± 0.6
|
Image reconstruction (processing)
Data were transferred to and processed on a dedicated separate prototype 4th generation iterative reconstruction (IR) system (iDose4, Philips Healthcare, Netherlands). This system is a hybrid IR algorithm that operates
in both the raw data and the image data domain, thereby reducing streak artifacts
caused by photon starvation and image noise. It offers seven different level settings,
defining the strength of the IR algorithm. Increasing iDose4 levels indicate an increasing strength of noise reduction (range: 11 – 55 % noise
reduction relative to a corresponding FBP reconstruction). The level can be defined
independently from the radiation dose at which an acquisition is performed. In addition,
iDose4 provides a feature named “multi-resolution”, which is a multi-frequency noise removal
technique that lowers the overall noise while closely preserving the desired frequency
spectrum characteristic of a corresponding routine-dose FBP image to preserve the
image texture and maintain an image appearance that is familiar to clinicians [19].
The raw dataset of each CCTA was processed 16 times resulting in n = 30 patients × 16
reconstructions = 480 image datasets using filtered back-projection (FBP) and 4 levels
of an advanced IR technique providing an incremental rate of IR (iDose level 2, 4,
6 and 7). For higher levels of IR (iDose level 4 and above), processing was performed
both without and with a “multi-resolution” feature. In addition, two different cardiac
reconstruction kernels (CB: cardiac standard; XCB: cardiac standard with edge enhancement)
were used with FBP and each IR level, respectively. Both kernels are used for cardiac
imaging. By using an XCB kernel, additional vessel wall enhancement can be achieved.
Axial 0.8 mm images were reconstructed as well as straight and curved multi-planar
reformations (MPR), and a 3 D reconstruction in volume rendering technique (VRT),
respectively.
Image analysis
The objective image quality was evaluated in all 30 datasets as previously described
in detail [2]. The following measurements were obtained by one reader (A.H.B.) using 0.8 mm thick
axial images. Circular regions of interest (as large as possible, 2 – 4 mm2) were drawn in the lumen of the coronary arteries and the adjacent epicardial fatty
tissue in order to derive the contrast-to-noise ratio (CNR) from the corresponding
CT numbers in nine locations: left main coronary artery (LM), proximal and distal
(distal to the second diagonal branch) left anterior descending coronary artery (LAD),
proximal first diagonal branch (D1), proximal and distal left circumflex coronary
artery (LCX), first obtuse marginal branch (OM1), proximal and distal (proximal to
the origin of the posterior descending coronary artery) right coronary artery (RCA).
A circular region of interest (100 mm2) was placed in the contrast-enhanced lumen of the aortic root to measure the image
noise by determining the standard deviation of CT numbers [20]
[21]. The contrast-to-noise ratio (CNR) was determined for all 9 coronary locations by
the following formula as described previously [2]:
contrast-to-noise ratio = (CT number coronary lumen [HU]−CT number adjacent tissue
[HU]) / image noise [HU].
In addition, datasets of 11 patients (n = 4 without coronary abnormalities, n = 3
with coronary stenosis, n = 2 with coronary stents, n = 2 with bypass grafts) were
transferred to an offline workstation (Brilliance Workspace 4.5, Philips, Best, Netherlands).
The subjective image quality was evaluated in all 16 different reconstructions of
these datasets by three independent readers (M.C., P.K., A.H.B.) with different levels
of experience in cardiac imaging (10, 7 and 2 years, respectively). The readers were
blinded to the level of IR. Based on the 18-segment model of the Society of Cardiovascular
Computed Tomography, subjective scores were given for every segment using a four-point
scale (1 = excellent image quality: “classic” image appearance, no or minimal artifacts;
2 = good image quality: slight artifacts, artificial image appearance; 3 = moderate
image quality: artifacts mainly due to noise, but evaluable concerning the presence
of stenosis; 4 = unevaluable). The main criteria of subjective image quality were
“classic” image appearance (CT image appearance as known by and familiar to radiologists)
and artifacts due to noise.
Radiation dose
The volume CT dose index (CTDIvol) and dose-length product (DLP) were obtained for
all scans using the dose exposure record generated by the scanner. Additionally, the
patient’s effective dose (mSv) according to ICRP 60 was estimated using the DLP method
with a conversion factor k = 0.014 mSv / mGy × cm [22].
Statistical analysis
The statistical analysis was performed using commercially available software (SPSS,
20.0, Inc., Chicago, IL, USA; Microsoft Excel, Redmond, WA, USA). Continuous data
are expressed as mean ± SD. Differences of CNR and subjective image quality among
different levels of IR and different reconstruction kernels were examined using one-way
analysis of variance (ANOVA). A two-tailed p-value < 0.05 was considered statistically
significant. Fleiss kappa with correction according to Brennan and Prediger was determined
for interobserver agreement of subjective image quality. The coefficient represents
concordance, where 1 is perfect agreement and 0 is no agreement at all.
Results
Patient characteristics
The mean heart rate during the scan was 56.5 ± 5.7 bpm (range 45 – 68 bpm). A dose
of 10.0 mg i. v. metoprolol was administered to two (6.7 %) of the patients. A mean
flow rate of 5.1 ± 0.2 ml/s for a mean amount of 73 ± 6 ml of contrast agent was injected.
Radiation dose
The dose-related parameters of the 30 CCTA scans in this study are listed in Table 2. The mean z-axis scan length was 12.7 ± 6.2 cm. The mean DLP for the 30 single prospectively
triggered CCTA acquisitions was 124 ± 46 mGy × cm corresponding to an estimated effective
dose of 1.7 ± 0.7 mSv (range 0.9 – 3.0; conversion factor 0.014 mSv / mGy × cm). Patients
with a BMI < 25 demonstrated a mean effective dose of 1.2 ± 0.4 mSv for CCTA (range
0.9 – 2.1).
Objective image quality
The average CT numbers were as follows: 520 ± 121 HU (aortic root, range 312 to 796
HU), 432 ± 123 HU (coronaries, range 130 to 838 HU) and –91 ± 15 HU (adjacent epicardial
fatty tissue, range –19 to –146 HU). While the CT numbers in the aortic root (ROI
size: 100 mm2) remained constant (within ± 1 HU), the corresponding CT numbers in the coronaries
(ROI size: 1 – 2 mm2) were somewhat shifted towards lower values with increasing iDose levels: by –10
and –4 on average for kernel CB (w/o and with multi-resolution, respectively), and
by –19 and –7 on average for kernel XCB (w/o and with “multi-resolution”, respectively).
The mean CNR of all measured locations in all reconstructions was 21.5 ± 5.3. The
mean CNR of all nine examined regions of the coronary arteries with respect to FBP
and the different levels of IR are shown for the CB kernel in [Fig. 1A] and for the XCB kernel in [Fig. 1B]. The mean CNR was significantly improved with IR when compared to FBP and with every
increasing level of IR (range CNR: 14.2 – 27.8; p < 0.001) with the best objective
IQ at the highest level of IR (iDose level 7) ([Fig. 1]). When using the CB kernel, the CNR was significantly higher compared to the XCB
kernel at FBP and iDose level 2, 4 and 6. At iDose level 7 the differences failed
statistical significance ([Fig. 2]). At the highest level of IR (iDose level 7), the “multi-resolution” feature led to
a further significant improvement in the CNR (32.9; p < 0.001) ([Fig. 3]).
Fig. 1 CNR values at different levels of IR. Significant improvement of CNR was found for
IR when compared to FBP and for every increasing level of IR when using CB kernel
(A) or XCB kernel (B).
Abb. 1 CNR-Werte bei unterschiedlichen IR-Stufen. Signifikante Verbesserung des CNR bei
IR im Vergleich zur FBP und für jede aufsteigende IR-Stufe unter Verwendung eines
CB-Faltungskerns (A) oder XCB-Faltungskerns (B).
Fig. 2 Comparison of CNR and subjective image quality for CB kernel and XCB kernel, respectively.
The CNR was significantly better for CB kernel at FBP (A), iDose level 2 (B), level 4 (C) and level 6 (D) as compared to XCB kernel. With respect to the subjective scores, however, the XCB
kernel was superior to the CB kernel (A–D).
Abb. 2 Vergleich der CNR und der subjektiven Bildqualität für den CB und XCB-Faltungskern.
CNR war significant höher für CB bei FBP (A), iDose Stufe 2 (B), 4 (C) und 6 (D) im Vergleich zum XCB-Faltungskern. Hinsichtlich der subjektiven Bildqualität war
allerdings der XC-Faltungskern überlegen (A–D).
Fig. 3 Effect of the “multi-resolution” feature on image quality. A significant improvement
in the CNR and subjective IQ is shown at the highest level of IR (iDose 7) (p < 0.001).
Abb. 3 Auswirkungen der „multi-resolution“ Funktion auf die Bildqualität. Ein signifikanter
Anstieg der CNR und subjektiven Bildqualität zeigt sich bei höchster IR Stufe (iDose
7) (p < 0.001).
Subjective image analysis
In 11 patients coronary artery segments were analyzed for subjective image quality.
Each of these segments was scored in all 16 reconstructions resulting in 5829 scores.
An image quality score of 1 (“excellent”) was given 1024 times (17.6 %), a score of
2 (“good”) 2933 times (50.3 %), a score of 3 (“moderate”) 1747 times (30.0 %), and
4 “unevaluable” was scored 125 times (2.1 %).The predominant reasons for “unevaluable”
segments given by the observers were motion, noise, or streak artifacts due to extensive
calcifications.
When using the CB kernel, the mean rating score over all patients and segments was
2.4 ± 0.5 for FBP, 2.3 ± 0.6 for iDose level 2, 2.1 ± 0.7 for iDose level 4, 2.4 ± 0.6
for iDose level 6 and 2.8 ± 0.6 for iDose level 7, respectively ([Fig. 4A]). When using the XCB kernel, the mean rating score for all patients and segments
was 2.3 ± 0.5 for FBP, 2.0 ± 0.7 for iDose level 2, 1.7 ± 0.7 for iDose level 4, 2.1 ± 0.5
for iDose level 6 and 2.6 ± 0.6 for iDose level 7, respectively ([Fig. 4B]).
Fig. 4 Subjective image quality at FBP and increasing levels of IR for CB kernel (A) and XCB kernel (B), respectively. Best subjective scores were reached at a medium level of IR (iDose
level 4) as compared to FBP and to the highest levels of IR.
Abb. 4 Subjektive Bildqualität bei FBP und ansteigenden Stufen der IR bei CB (A) und XCB (B). Beste subjektive Scores wurden bei mittleren IR-Stufe (iDose Stufe 4) erreicht.
The subjective IQ was rated best at a medium level of IR (iDose level 4) with significant
improvement for IR when compared to FBP (p < 0.0001) and a more “classic” appearance
of images compared to high levels of IR (p < 0.001) ([Fig. 4], [5]). For FBP and each level of IR, the subjective IQ score was better when using the
XCB kernel when compared to the CB kernel reconstructions ([Fig. 2]).
Fig. 5 Image examples. Axial (A–C) CT images of the aortic root and proximal RCA and curved MPRs of the RCA (D–F) in a 57-year-old male, demonstrating moderate subjective image quality (score 3)
after FBP with kernel XCB (A, D), excellent image quality (score 1) at medium level (iDose 4 with XCB) of IR (B, E) and good image quality (score 2) at highest level (iDose 7 with XCB) of IR (C, F).
Abb. 5 Bildbeispiele. Axiale (A–C) CT-Bilder der Aortenwurzel und proximalen RCA sowie gekrümmte MPRs der RCA (D–F) bei einem 57-jährigen Patienten, die eine moderate subjektive Bildqualität (Score
3) bei FBP und XCB zeigen (A, D), eine exzellente Bildqualität (Score 1) bei mittlerer IR-Stufe (iDose 4 mit XCB)
(B, E) und eine gute Bildqualität (Score 2) bei höchster Stufe (iDose 7 mit XCB) (C, F).
When using the “multi-resolution” feature and CB kernel, the mean score for all patients
and segments was 1.7 ± 0.6 for iDose level 4, 2.6 ± 0.6 for iDose level 6 and 2.9 ± 0.5
for iDose level 7, respectively, showing a significant improvement at iDose level
4 (p < 0.001) only. When combining the multi-resolution feature and the XCB kernel,
the mean rating score for all patients and segments was 1.4 ± 0.5 for iDose level
4, 1.6 ± 0.6 for iDose level 6 and 1.8 ± 0.6 for iDose level 7, respectively, showing
a significant improvement at all three levels (p < 0.001) ([Fig. 3]).
The three radiologists demonstrated a substantial interobserver agreement regarding
the subjective image quality (average Fleiss kappa with correction according to Brennan
and Prediger of 0.74 ± 0.12).
A combined illustration of subjective and objective IQ with respect to the different
IR levels is demonstrated in [Fig. 2]. Examples of subjective image quality scoring (moderate, good, and excellent) at
different IR levels are shown in [Fig. 5].
Discussion
The present study demonstrates that increasing the levels of an advanced IR technique
has the potential to essentially improve subjective and objective image quality in
dose-optimized CCTA examinations in the clinical routine.
Radiation dose has raised increasing concern in modern radiology. Radiation exposure
due to cardiac CT has been significantly reduced during the last years by implementation
of various technical innovations [7]
[8]
[9]
[10]
[11]. However, dose reduction may compromise image quality, which remains the critical
parameter in all “low-dose” examinations. The main drawback of FBP as a standard image
reconstruction technique in CT is the rapidly increasing image noise relative to the
effective radiation with the risk of non-diagnostic image quality due to photon starvation.
A disproportional dose reduction resulting in non-diagnostic scans, however, must
be avoided as the patient may be exposed to ionizing radiation without any benefit.
In this study, a CCTA protocol with optimized dose-related parameters was employed.
The estimated mean effective dose (according to ICRP 60) of 1.7 ± 0.7 mSv was in the
same range as in previous studies [11]. Using the high-pitch mode on a dual-source CT unit, the mean effective dose for
small and average-sized can even be reduced below 1 mSv [23]
[24].
All examinations of our study were fully diagnostic, even when conventional FBP was
used for image reconstruction. When the advanced IR technique was applied, however,
the objective and subjective image quality was significantly improved. The CNR was
almost doubled at the highest level of IR when compared to FBP in our measurements.
Many studies have been published within the last years reporting on noise reduction
and improvement of low-contrast image quality due to IR in CT examinations of the
abdomen [13], the thorax [14]
[15] and the heart [25]
[26]
[27]. In recent studies by Utsunomiya et al. and Laqmani et al., a progressive improvement
of the CNR and subjective image quality in cardiac CT and low-dose chest CT was reported
when using different levels of IR compared to FBP [28]
[29].
Regarding objective image quality (noise, CNR), these results were quite concordant
with the present study as the best CNR and the most effective noise reduction were
observed at the highest level of IR (iDose level 7). Although a slight decrease in
contrast between coronaries and adjacent epicardial fatty tissue was noted with increasing
IR levels, the corresponding reduction in noise by far outweighs this effect, which
is only observed in measurements using ROIs of very small size. Advanced IR algorithms
enable a progressive separation of image information and noise. Due to the involvement
of the raw data space in the reconstruction process, those IR techniques are not only
capable of reducing image noise (domain of image space) but can also reduce and prevent
image artifacts (domain of raw data space) to further improve image quality.
In contrast to other studies, a discrepancy between the subjective and objective image
quality at increasing levels of IR was found in this study. While the highest CNR
values were measured at the highest level of IR, the best subjective image quality
was found at a medium level of IR (iDose level 4). In this setting, noise-related
artifacts were substantially reduced. In contrast to the highest levels of IR, however,
the authentic CT image appearance, which the readers were used to from daily practice,
was preserved at a low and medium level of IR. In a previous study using less advanced
IR algorithms, differences in image appearance due to higher levels of IR have already
been discussed [30]. Compared to FBP, CT images reconstructed using iterative algorithms may appear
more “artificial” or “plastic” mainly due to a general smoothing effect and a loss
of granular image appearance. This is true particularly for CT images acquired with
a lower dose subjectively assigning radiation saving parameters to a grainier image
appearance. Singh et al. describe a blotchy pixelated image impression when reporting
about abdominal CT images using an adaptive IR technique [13]. The results of our systematic comparison of different levels of IR reflect the
daily experience when dealing with IR. The image appearance of IR is different from
images processed by FBP which radiologists are used to. However, it has to be emphasized
that the image quality scores reported here represent the highly subjective image
impression of the three readers in this study and may be different when other radiologists
score the images. When using advanced hybrid IR, noise texture and spatial resolution
were reported as constant by Utsunomiya et al., although slight differences between
image texture between FBP and IR were described [28]. In our study, differences in the subjective image quality between the medium and
high level of IR were found to be significant in favor of a medium level of IR leading
to an improvement of almost 25 %. As a possible reason for the modified non-classic
image appearance after IR, changes in the noise power spectrum (NPS) due to an alteration
in raw data computing are discussed in the literature [31]. Particularly at lower frequencies, IR may influence noise characteristics. Whether
this is the only key to explain the differences in subjective image impression has
to be further clarified. Results for the “multi-resolution” feature described above,
which modifies the NPS to preserve a typical CT image appearance, support this hypothesis
as “multi-resolution” led to further improvement of the subjective IQ in higher levels
of IR. However, this applies only in combination with the sharper XCB kernel, indicating
that different forms of IR have to be used with particular respect to the characteristics
of the reconstruction kernel in order to keep subjective image quality at an ideal
level taking the requirements of the radiological task into account.
Regarding the two reconstruction kernels CB and XCB applied in this study, results
for objective and subjective image quality differed slightly but significantly. Whereas
the CNR of images processed with the CB kernel exceeded the CNR values of images generated
with the edge-enhanced XCB kernels, the application of XCB led to better subjective
image scores. The XCB kernel is used in order to produce more edge and vessel wall
enhancement than can be achieved with the CB kernel. This not only compensates the
increased noise from the XCB kernel but results in a better overall subjective image
quality already with FBP. Thus, IR in combination with an edge-enhancing reconstruction
algorithm (i. e. XCB) and “multi-resolution” represents an ideal combination, as high
spatial resolution can be combined with a reduction in image noise while preserving
an easy-to-adapt image appearance.
The results of our study are in good agreement with those from a similar study performed
with the iDose prototype, which, however, was restricted to a maximum iDose level
of 5 and the use of the XCB kernel only [32]. As a prototype that was not approved as a medical device was used at the point
in time when this study was conducted, only the influence of increasing IR levels
on image quality at a constant dose could be investigated. Although the results indicate
that the improvements in image quality could be used for dose reductions at constant
subjective image quality, it is not possible to state how large this reduction could
be. However, as iDose has become a regular medical device in the meantime, this could
be evaluated in an additional study.
Our study has some limitations. Firstly, as a retrospective analysis of clinical data
was performed, a systematic bias cannot be totally excluded. Secondly, a systematic
comparison of CCTA and invasive coronary angiography as a reference standard has not
been performed in this study, so that a possible influence of CCTA with different
IR levels on diagnostic accuracy could not be analyzed. Furthermore, only 11 of 30
patients were included for subjective image analysis, although this number is similar
to comparable previously published series and these datasets represent the spectrum
of cardiac patients in the clinical routine (normal coronaries, stenosis, stents and
bypass grafts were included). Moreover, the results of subjective IQ analysis were
very stable and a substantial change was not to be expected by expanding the analysis
to all datasets. The CCTA protocol was not completely identical in all patients as
the flow rate and amount of contrast as well as the z-coverage were adjusted individually
in every patient. The study population itself was not homogeneous regarding BMI, heart
rate, and thoracic diameters but reflects consecutive patients in the clinical routine.
On the other hand, FBP and all levels of IR were performed on the same datasets. Radiation
doses were calculated and not measured directly in this study. As the IR system of
only one manufacturer was used in this study, the results cannot be automatically
transferred to other IR systems of other manufacturers.
In conclusion, objective image quality progressively improves with increasing level
of IR in dose-optimized CCTA with the best CNR values at the highest level of IR.
The best subjective image quality, however, is achieved at medium levels of IR due
to reduced artifacts and a preserved “classic” image appearance. The use of edge-enhancing
reconstruction algorithms combined with a medium level of iterative reconstruction
in combination with the NPS preserving “multi-resolution” feature proved to result
in superior image quality in low-dose CCTA suggesting application in the clinical
routine.
Clinical relevance
Advanced iterative reconstruction techniques offer different increasing levels of
IR. In low-dose CCTA, a medium level of iterative reconstruction combined with an
edge-enhancing kernel leads to optimal subjective image quality suggesting application
in clinical practice. Higher levels of IR further increase the objective image quality
(CNR) but may affect the “classic” image appearance. Here, a combination with a “multi-resolution”
feature can help to preserve the NPS.
