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Original Research Article

Patient-specific predictors of image noise in coronaryCT angiography

Annika Schuhbaeck MDa,b,*, Marcella Schaefer b, Mohamed Marwan MDb,Soeren Gauss MDb, Gerd Muschiol RTb, Michael Lell MDb, Tobias Pflederer MDb,Dieter Ropers MDb, Johannes Rixe MDa, Christian Hamm MDa, Werner G. Daniel MDa,Stephan Achenbach MDa,b

aDepartment of Cardiology, University of Gießen, Klinikstr. 33, 35392 Gießen, GermanybDepartments of Cardiology and Radiology, University of Erlangen, Germany

a r t i c l e i n f o

Article history:

Received 5 March 2012

Received in revised form

2 August 2012

Accepted 5 October 2012

Available online 24 January 2013

Keywords:

Coronary CT angiography

Image noise

Tube voltage

Dual-source CT

Conflict of interest: The authors report no cThis study was supported by the GermanMedical Valley).* Corresponding author.E-mail address: annika.schuhbaeck@inne

1934-5925/$ e see front matter ª 2013 Sociehttp://dx.doi.org/10.1016/j.jcct.2012.10.011

a b s t r a c t

Background: Coronary computed tomography (CT) angiography can be associated with high

radiation exposure. Reduction of tube voltage from 120 kV to 100 kV can reduce the dose by

up to 40%, but it also increases image noise.

Objective: We aimed to find a patient-specific predictor of image noise to determine the use

of reduced tube voltage.

Methods: Contrast-enhanced coronary dual-source CT angiography data sets [prospectively

electrocardiogram (ECG)etriggered axial and retrospectively ECG-gated spiral acquisition,

rotation of 280 milliseconds, 2 � 128 � 0.6 mm collimation, 100 kV, 320 mAs] of 165 patients

(age, 54 � 13 years) for the detection of coronary artery stenoses were analyzed. Image

noise was measured in the aortic root. Influence of body weight, height, body mass index,

thoracic cross sectional area, as well as the area of the thoracic solid tissue were analyzed.

Results: Mean image noise in the aorta was 35.1 � 8.9 HU. Mean dose length product was

207 � 184 cm $ cGy with an average effective dose of 2.9 � 2.6 mSv. The patient cohort was

divided into tertiles according to image noise. Numerous parameters, including BMI and

body weight, were significantly different between the highest and lowest tertiles. In

multivariable regression analysis, the area of the thoracic solid tissue was the only inde-

pendent predictor of image noise (P < 0.0001).

Conclusions: The area of the thoracic solid tissue at the level of the aortic root predicts image

noise and may hence be used for the decision to reduce tube voltage from 120 kV to 100 kV.

ª 2013 Society of Cardiovascular Computed Tomography. All rights reserved.

1. Introduction Several clinical indications for coronary CT angiography

Coronary CT angiography permits the detection of coronary

artery stenoses with high sensitivity and specificity.1e8

onflicts of interest.government, Bundesmin

re.med.uni-giessen.de (Aty of Cardiovascular Com

have been identified. The main indication for coronary CT

angiography is to rule out significant coronary artery stenoses

in symptomatic patients with an intermediate likelihood for

isterium fur Bildung und Forschung (01EX1012B, Spitzencluster

. Schuhbaeck).puted Tomography. All rights reserved.

J o u r n a l o f C a r d i o v a s c u l a r C om p u t e d T omog r a p h y 7 ( 2 0 1 3 ) 3 9e4 540

coronary artery disease.9 The future event rate in symptom-

atic patients with a “negative” coronary CT angiogram is

extremely low.10e14 Coronary CT angiography can be per-

formed with high patient comfort and a low rate of acute

complications.15,16 However, it can be associated with high

radiation exposure.17,18 By contrast, new image acquisition

protocols enable the performance of coronary CT angiography

with substantially reduced radiation exposure. With some

acquisition protocols, estimated effective doses of <1.0 mSv

are achievable in selected patients.19 Among the parameters

that can be adjusted to lower radiation exposure, reductions

in tube current and reductions in tube voltage are often used.

For example, reducing tube voltage from 120 kV to 100 kV tube

voltage can reduce the dose by up to 40%.18,20e25 However,

reduction of tube current or voltage leads to higher image

noise.23,25e27 Increased image noise may compromise diag-

nostic accuracy; therefore, the use of low-dose acquisition

protocols needs to be tailored to the individual patient to avoid

unacceptable high image noise. Understanding is poor about

the relation between patient characteristics and image noise,

and suitable predictors of image noise have been identified.

Several patient-specific parameters such as body weight or

body mass index (BMI; calculated at weight in kg divided by

height in m2),28,29 patient circumference,30,31 patient chest

area, patient chest attenuation,31 patient transverse chest

diameter,32 and x-ray attenuation in the scout view33 have

been studied so far and have shown a relation to image noise

or image quality. It is currently unknown which parameter

may be the optimal patient-specific discriminator to deter-

mine the use of low-dose acquisition protocols.

The aim of our study was to analyze the effect of several

parameters, including the area of the thoracic cross section

and the area of the thoracic solid tissue, on image noise.

2. Methods

Between January 2010 and May 2011, we included 165

consecutive patients with known or suspected coronary

artery disease with a body weight <100 kg referred for coro-

nary CT angiography after having given informed consent at

the Department of Cardiology at the University Hospital of

Erlangen. Approval for the study and analysis was obtained

from the institutional review board. Data on body weight,

height, and cardiovascular risk factorswere collected from the

patients’ medical history.

Patients presenting with a heart rate >65 beats/min

received 50 or 100 mg of atenolol orally at least 30 minutes

before the CT scan. If heart rate remained at >65 beats/min in

inspiration, up to 30 mg of metoprolol was injected intrave-

nously, using repeated 5-mg doses before CT. Before coronary

CT angiography, all patients received 0.8 mg of glycerol trini-

trate sublingually.

Imaging was performed on a dual-source CT scanner

(Definition Flash; Siemens Healthcare, Forchheim, Germany;

280-millisecond rotation, 2 � 128 � 0.6 mm collimation) in

deep inspiration. For all patients, tube voltage was set to

100 kV and tube current was 320 mAs.

A “test bolus” protocol was used. Iodinated contrast (10 mL;

iomeprol, Iomeron350;BraccoAltanaPharmaGmbH,Konstanz,

Germany) were injected at a flow rate of 5 mL/s, followed by 50

mL of saline at the same flow rate. The time to peak enhance-

ment in the ascending aortawasmeasuredwith a series of axial

scans acquired in 2-second increments, with the first image

being acquired 15 seconds after the start of injection. For the

coronaryCTangiography, 60mLof contrastagentwere injected,

followed by a 60-mL flush (consisting of 80% saline and 20%

contrast), bothat thesameflowrateof6mL/s. Imageacquisition

wasstartedwithadelay thatcorrespondedto thecontrast agent

transit time plus 2 seconds. Coronary CT angiography data sets

were acquired with the use of either prospectively electrocar-

diogram (ECG)etriggered axial or retrospective ECG-gated spiral

acquisition, depending on heart rate.

2.1. CT image reconstruction

CT angiography images were reconstructed with filtered back

projection with 0.6-mm slice thickness and an increment of

0.3 mm with the use of a medium smooth reconstruction

kernel (“B26f”). In prospectively ECG-triggered axial acquisi-

tion, only one time instant in the cardiac cycle was available

for image reconstruction (70% of the R-R interval). In retro-

spectively ECG-gated spiral acquisition, an automatic algo-

rithm detected the optimal phase for image reconstruction in

diastole or systole (mean, 68% of the R-R interval). CT images

for the measurement of the area of the thoracic cross section

and the thoracic solid tissue were reconstructed from the

same rawdatawith a full field of view of the entire thoraxwith

3-mm slice thickness and an increment of 1.5 mm with the

use of a very sharp reconstruction kernel (“B70f”).

2.2. Measurement of the area of the thoracic crosssection and the thoracic solid tissue

CT data sets were transferred to an off-line workstation

(Multimodality Workplace; Siemens Healthcare). The area of

the thoracic cross section and the area of the thoracic solid

tissue were manually measured at the level of the aortic root

(Fig. 1). The thoracic solid tissue was defined as the area of the

thoracic cross section minus the lung/mediastinum area.

2.3. Image noise

Image noise was measured with the SD of CT attenuation

values in a circular region of interest (3.5 cm2) set in the aortic

root in the coronary CT angiography data set (Figs. 2 and 3).

2.4. Effective radiation dose

The effective radiation dose was derived from the product of

the dose length product (DLP) and a conversion factor of 0.014

for chest CT in adults according to Bongartz et al.34

2.5. Statistical methods

Statistical analyses were performed with SPSS for Windows

release 18.0 (SPSS Inc, Chicago, II, USA) and GraphPad Prism

version 5.01 (GraphPad Software, San Diego CA, USA). Data are

expressed as means � SDs and ranges for continuous vari-

ables. The whole patient cohort was divided into tertiles

according to image noise. Bodyweight, height, BMI, the area of

J o u rn a l o f C a r d i o v a s c u l a r C om p u t e d T omog r a p h y 7 ( 2 0 1 3 ) 3 9e4 5 41

the thoracic cross section, the area of the thoracic solid tissue,

as well as the corresponding mean CT densities of the tertiles

were compared with each other. A Mann-Whitney U test was

used to test for statistical significance. P values <0.05 were

considered to be statistically significant. Multivariable

regression analysis was performed, including all parameters

that had a significant difference between the tertiles of image

noise in univariable analysis.

3. Results

Of 165 patients (age, 54 � 13 years), 87 were men and 78 were

women. Prospectively ECG-triggered axial acquisition was

Figure 1 e Prospectively electrocardiogram-triggered axial

acquisition in a 66-year-old female (66 kg, 165 cm, BMI 24).

(A) Measurement of the area of thoracic cross section. (B)

Measurement of the area of thoracic solid tissue.

Figure 2 e Measurement of image noise at the level of the

aortic root in a 49-year old male (51 kg, 160 cm, patient of

the first tertile).

performed in 112 patients, and spiral acquisition with retro-

spective ECG-gating was performed in 53 patients. Clinical

data are shown in Tables 1 and 2. Mean heart rate during

coronary CT angiography was 61 � 10 beats/min (range,

41e129 beats/min). Mean DLP was 208 � 184 mGy $ cm which

corresponds to an average effective dose of 2.9 � 2.6 mSv

(range, 1.0e16.2 mSv). In all 165 patients, the mean attenua-

tion in the ascending aorta was 518.1 � 95.5 HU with a corre-

sponding mean image noise of 35.1 � 8.9 HU.

Patients were divided in tertiles according to image noise,

with the first tertile ranging from 20.9 to 31.0 HU, the second

tertile from 31.2 to 36.3 HU, and the third tertile from 36.6 to

72.5 HU. Detailed results are shown in Table 2.

Figure 3 e Measurement of image noise at the level of the

aortic root in a 57-year-old man (94 kg, 179 cm, patient of

the third tertile).

Table 1 e Patient characteristics.

Values

Age, y, mean � SD 54 � 13

Sex, male, n/N (%) 87/165 (53)

Body mass index, mean � SD 25 � 3

Risk factors, n/N (%)

Hypertension 70/165 (42)

Diabetes 6/165 (4)

Hypercholesterolemia 86/165 (52)

Smoking 27/165 (16)

Family history of coronary artery disease 67/165 (41)

J o u r n a l o f C a r d i o v a s c u l a r C om p u t e d T omog r a p h y 7 ( 2 0 1 3 ) 3 9e4 542

In the first tertile, 33 patients were examined with

prospectively ECG-triggered axial acquisition and 22 patients

with spiral acquisition with retrospective ECG-gating. In the

second tertile, 36 patients were examined with prospectively

ECG-triggered axial acquisition and 19 patients with spiral

acquisition with retrospective ECG-gating. In the third tertile,

43 patients were examined with prospectively ECG-triggered

axial acquisition and 12 patients underwent spiral acquisi-

tion with retrospective ECG-gating.

Patient height and heart rate did not differ significantly

between the tertiles. The mean age of the patients in the third

tertile was significantly higher than in the first tertile

(P ¼ 0.02). Patient weight, BMI, and area of the thoracic cross

section did not differ significantly between the first and

second tertiles, but did differ significantly between the second

and the third tertiles and between the first and the third ter-

tiles (see Table 2), respectively. For the area of thoracic solid

tissue, a statistically significant difference was observed

between all tertiles with higher areas of the thoracic solid

tissue in the tertiles with higher image noise. The mean

attenuation in the ascending aorta was not significantly

different between the tertiles.

Multivariable regression analysis included body weight,

height, BMI, the area of the thoracic cross section, and the area

of thoracic solid tissue (Table 3). The area of thoracic

solid tissue was the only independent predictor of image

noise (P < 0.0001, R ¼ 0.067, 95% CI: 0.055e0.079).

Table 2 e Clinical data.

All patients 1st Tertile(�31.0 HU)

2nd Ter(31.2e36.3

No. of patients 165 55 55

Age, y 54 � 13 51 � 12 55 � 1

Weight, kg 74 � 12 71 � 12 72 � 1

Height, cm 171 � 9 171 � 9 172 � 9

BMI 25 � 3 24 � 3 24 � 2

Heart rate, beats/min 61 � 10 63 � 13 61 � 1

Area of the thoracic

cross section, cm2

732 � 116 687 � 97 706 � 1

Area of thoracic

solid tissue, cm2

382 � 87 335 � 63 361 � 6

Mean attenuation in the

ascending aorta, HU

518 � 96 496 � 101 531 � 9

BMI, body mass index (calculated at weight in kg divided by height in m2

Values are expressed as mean � SD.

4. Discussion

The relation between radiation exposure and image noise is of

importance in coronary CT angiography and receives specific

attention in the context of low-dose image acquisition

protocols. In agreementwith previous studies, wewere able to

show that numerous patient-specific parameters have an

effect on image noise in coronary CT angiography. Body

weight and BMI have previously been identified as predictors

of image noise28,29,35 and were confirmed in our trial, but they

are conceivably of limited value to predict the noise in coro-

nary CT angiography data sets, because the latter is mainly

influenced by the amount and attenuation of body tissue

specifically in the chest and not remote parts of the body. We

therefore specifically evaluated the influence of the thoracic

cross section and the area of thoracic solid tissue,measured at

the level of the aortic root, on image noise and could show

a significant correlation. In fact, multivariable regression

analysis showed that the area of thoracic solid tissue at the

level of the aortic root was the only independent predictor of

image noise. This area can easily be obtained manually from

nonenhanced coronary calcium studies acquired before

coronary CT angiography, from transaxial scout images, or

from images acquired for the purpose of determining the

contrast agent transit time and is therefore readily available

before data acquisition in patients who undergo coronary CT

angiography.

Similar parameters have been used by others to determine

image noise or to make decisions about the use of low-dose

image acquisition protocols. Recently, Goshhajra et al31

showed that the area of thoracic cross section at the level

of the mid left atrium strongly correlated with BMI and that

BMI was poorly suited to select 120 kV versus 100 kV tube

voltage for coronary CT angiography.31 However, they did not

specifically analyze image noise. Rogalla et al36 showed that

the anterior-posterior chest diameter assessed from the

lateral scout view was an appropriate method to adapt the

tube current in coronary CT angiography while image quality

could be preserved.36 Gao et al33 could show that

tileHU)

3rd Tertile(�36.6 HU)

P

1st vs 2ndtertiles

2nd vs 3rdtertiles

1st vs 3rdtertiles

55

3 57 � 13 NS NS 0.02

1 79 � 12 NS 0.0019 0.0005

172 � 10 NS NS NS

27 � 3 NS 0.0001 <0.0001

0 59 � 7 NS NS NS

10 802 � 109 NS <0.0001 <0.0001

4 450 � 86 0.029 <0.0001 <0.0001

4 528 � 882 NS NS NS

); NS, not significant.

Table 3 e Univariate and multivariable predictors ofimage noise.

UnivariateP value

MultivariableP value

Weight, kg <0.0001 0.06

Height, cm 0.48 0.57

BMI, <0.0001 0.05

Area of thoracic

cross section, cm2

<0.0001 0.74

Area of thoracic

solid tissue, cm2

<0.0001 <0.0001

BMI, body mass index (calculated at weight in kg divided by

height in m2).

J o u rn a l o f C a r d i o v a s c u l a r C om p u t e d T omog r a p h y 7 ( 2 0 1 3 ) 3 9e4 5 43

individualized tube current selection according to the CT

attenuation of the scout view allowed radiation dose reduc-

tion without compromising image quality.33 Recently, Win-

klehner et al37 evaluated an automated attenuation-based

tube potential selection that was based on the attenuation

along the patient’s longitudinal axis acquired by topogram

images for thoracoabdominal CT angiography. They could

show that this method reduced overall radiation dose by 25%

compared with standard 120 kV.37 Intuitively, our method of

directly measuring the area of thoracic solid tissue should be

the most direct method to determine the amount of tissue

attenuation that contributes to image noise. Ultimately,

however, its value in comparison with other methods must

be evaluated, and the clinical results when using this

parameter to determine image acquisition protocols must be

determined.

4.1. Limitations

Our study has several limitations. Body weight and BMI can

be assessed before the CT scan, whereas the area of the

thoracic cross section and the area of thoracic solid tissue

can only be assessed from CT images (eg, from images of the

calcium scoring or test bolus) and are therefore available only

immediately just before image acquisition. Potentially,

however, they could serve as a tool for automated algorithms

to select appropriate image acquisition parameters. In our

study, patients with a body weight of >100 kg were excluded,

so that adequate image quality with a tube voltage of 100 kV

could be expected. Cardiomegaly or pleural effusion could

also contribute to image noise but could not be included in

the measurement of thoracic solid tissue. Thus, the proposed

method of selecting tube parameters could lead to higher

image noise in such patients. Regarding the reconstruction

algorithm, iterative reconstruction was not used. Further-

more, we used 2 different data acquisition protocols:

a prospectively ECG-triggered axial and a retrospective ECG-

gated spiral acquisition mode. Influence of different scan-

ning protocols on image noise was not assessed and may

theoretically have an effect on image noise. However,

because we kept slice thickness and reconstruction kernels

constant, such an effect would likely be minimal. Finally, we

measured image noise but did not quantify overall image

quality.

4.2. Conclusions

Our study confirms the influence of several patient-specific

predictors on image noise in coronary CT angiography.

However, the cross-sectional area of thoracic solid tissue is

a newly identified and independent predictor of image noise

and may be a useful parameter to make decisions about the

use of image acquisition parameters to limit radiation expo-

sure, without compromising image quality, in coronary CT

angiography.

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