December 2010, VOLUME 195
NUMBER 6

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December 2010, Volume 195, Number 6

Cardiopulmonary Imaging

Original Research

Assessment of Agatston Coronary Artery Calcium Score Using Contrast-Enhanced CT Coronary Angiography

+ Affiliations:
1Department of Radiology, Leiden University Medical Center, C2-S, Albinusdreef 2, 2333 ZA Leiden, The Netherlands.

2Department of Cardiology, Leiden University Medical Center, The Netherlands.

Citation: American Journal of Roentgenology. 2010;195: 1299-1305. 10.2214/AJR.09.3734

ABSTRACT
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OBJECTIVE. The purpose of this article is to evaluate to what extent Agatston scores may be derived from CT coronary angiography (CTA) examinations, compared with traditional unenhanced CT calcium scores.

MATERIALS AND METHODS. Fifty patients with a CT calcium score–Agatston score of zero and 50 patients with a CT calcium score–Agatston score of 1 or greater whose CT calcium scores had been calculated and who had undergone CTA using volumetric 320-MDCT were included. Agatston scores were obtained at 3.0-mm slices for CT calcium score and CTA. Method agreement, interobserver agreement, and diagnostic performance of CTA for detecting coronary calcium were evaluated.

RESULTS. Of 50 patients with a positive CT calcium score–Agatston score, coronary artery calcium was detected with CTA in 43 patients by observer 1 (mean CTA score, 102 ± 202; mean CT calcium score, 254 ± 501) and in 46 patients by observer 2 (mean CTA score, 94 ± 147; mean CT calcium score, 272 ± 531). Of the 50 patients with a CT calcium score–Agatston score of zero, 49 (98%, observer 1) and 50 (100%, observer 2) had a zero score with CTA as well. An intraclass correlation of 0.78 and 0.62 was found between CT calcium score and CTA (p < 0.01), whereas higher Agatston scores were underestimated with CTA. For observer 1, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for detection of coronary calcium with CTA were 86%, 98%, 98%, 88%, and 92%, respectively, and the corresponding values for observer 2 were 92%, 100%, 100%, 93%, and 96%, respectively. Interobserver agreement was 0.996 for CT calcium score and 0.93 for CTA.

CONCLUSION. Coronary artery calcium can be detected on CTA images with high accuracy. The Agatston calcium score derived from CTA images shows good correlation with unenhanced CT calcium score and is highly reproducible. However, higher Agatston scores are systematically underestimated when derived from CTA images.

Keywords: Agatston score, coronary artery calcium, CT angiography, unenhanced CT

Introduction
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Coronary artery disease is one of the leading causes of death. Quantifying the amount of coronary artery calcium with unenhanced CT calcium score has been shown to be a reliable noninvasive technique for screening risk of future cardiac events [1, 2] and can be quantified by using the Agatston score [3] or scores such as the volume score [4] or calcium mass [5]. Large patient studies have shown that the amount of coronary artery calcium based on the Agatston score is a strong predictor for risk of myocardial infarction and sudden cardiac death, independently of conventional coronary risk factors [68].

Absent or low coronary artery calcium has been shown to be highly accurate in excluding coronary artery disease in asymptomatic patients [9, 10]. However, the value of a zero or low calcium score in symptomatic patients remains less clear. Several studies have reported the presence of obstructive (≥ 50%) noncalcified plaque in up to 8.7% of symptomatic patients with zero or low calcium scores [1114]. Therefore, in symptomatic patients, CT calcium score may be followed by CT angiography (CTA), or CTA may be performed alone.

CTA with the aid of IV contrast agent injection is widely used for the evaluation of suspected coronary artery disease. CTA confirms or excludes significant coronary artery stenosis with high accuracy compared with invasive coronary angiography [1517]. Furthermore, it has been shown that the presence of coronary artery disease detected with CTA is of incremental and independent value in predicting all-cause mortality in symptomatic patients [1820].

CTA allows visualization of the vessel lumen but also of the vessel wall, including calcified atherosclerotic plaque [21]. However, the level of contrast enhancement in the coronary vessels may obscure plaque and may obviate reliable measurements of plaque density, especially in noncalcified plaques. It is conceivable that the amount of coronary calcium may be estimated by using the CTA images owing to the relatively high density of calcified plaques compared with that of noncalcified plaques. Only a few studies have addressed this issue previously [2224]. To derive calcium scores from CTA, these studies increased the threshold values for coronary calcium from the standard (i.e., 130 HU) to 350 HU [22, 23] or even 600 HU [24], to avoid luminal contrast being falsely depicted as coronary artery calcium. The increase in attenuation threshold resulted in underestimation [22, 24] or overestimation of the calcium scores [23], whereas increasing threshold values may lead to decreased sensitivity for depicting small amounts of coronary calcium [25].

The purpose of this study was to evaluate to what extent Agatston scores may be derived from CTA examinations compared with traditional CT calcium score.

Materials and Methods
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Study Population

Fifty patients with an Agatston score of zero and 50 patients with a positive Agatston score (≥ 1) were, per group, consecutively selected from a database of patients who had undergone both unenhanced CT calcium score and contrast-enhanced CTA investigations for clinical indications (59 men and 41 women; mean age, 55 ± 11 years; height, 175 ± 20 cm; weight, 82 ± 15 kg). Patients with coronary stents (n = 5), pacemakers (n = 6), and prosthetic heart valves (n = 10) had been excluded beforehand to avoid scoring artifacts. Our institutional review board does not require its approval for anonymous retrospective technical analysis of data, as was the case in this study.

CT Protocol

All examinations were performed with a 320-MDCT scanner (Aquilion ONE, Toshiba). The patients had undergone prospectively ECG-gated unenhanced volumetric CT (to calculate CT calcium score) for scoring the amount of coronary calcium according to Agatston et al. [3] during the same session, followed by a prospectively ECG-gated contrast-enhanced volumetric CTA for coronary artery evaluation, with (n = 68) or without (n = 32) functional analysis. To lower the heart rate, 25–100 mg of oral metoprolol was administered to patients with a cardiac frequency exceeding 60 beats per minute, if no contraindications were present. Mean (± SD) heart rate during scanning was 54 ± 7 beats per minute.

The scan range was planned between the carina and cardiac apex. Depending on the expected scan range, a 320 × 0.5 mm or 280 × 0.5 mm detector configuration was used. Immediately before image acquisition, an optimal reconstruction phase was determined during a breath-hold exercise with ECG recording. Full cardiac CT calcium score acquisition was performed within a single heart beat during breath-hold at inspiration. Scan parameters were 120 kV tube voltage and 200–400 mA tube current (mean, 320 ± 49 mA), depending on patient size and shape (200 mA for small or thin patients, 250 mA for average size patients, and 300–400 mA for large or obese patients). Rotation time was 0.35 second. Effective radiation dose estimation was based on the dose–length product provided by the scanner for each patient and by using the correction factor 0.017 for chest imaging in adults [26]. The estimated dose was 1.9 ± 0.3 mSv.

CTA was performed after bolus injection of 50–70 mL of iodinated contrast agent (400 mg/mL iomeprol; Iomeron, Bracco) via antecubital vein injection with a flow rate of 5.0 mL/s followed by a 20 mL mix of 50% contrast agent and 50% saline, followed by a 25-mL saline flush using an automatic injector (Stellant CT, MedRad). Bolus tracking was performed by placing a region of interest in the left ventricle. Image acquisition was automatically started 7 seconds after reaching a predefined threshold difference of 100 HU. Scan parameters dependent on body mass index (BMI) were as follows: 100 kV and 450–550 mA for BMI 17–23 (15 patients); 120 kV and 400–580 mA for BMI 23–30 (65 patients); and 135 kV and 510 mA for BMI greater than 30 (20 patients). Mean BMI was 26 ± 4. Rotation time was 0.35 second. The scan range for CTA had been planned with the aid of the CT calcium score scan; care was taken to include the full range of the coronary arteries. Full cardiac CTA acquisition was performed within a single heartbeat during breath-hold at inspiration, with or without functional analysis, including dose modulation throughout the cardiac cycle. Estimated effective radiation dose was 10.7 ± 5.9 mSv.

Image Reconstruction

Standard reconstruction kernel filters were used for image reconstruction: FC12 for CT calcium score and FC43 for CTA. For CT calcium score, nonoverlapping 3.0-mm data sets were reconstructed, which is the standard method used in clinical practice based on electron-beam CT [3]. Similarly, for CTA, data sets of nonoverlapping 3.0-mm slices were reconstructed for evaluation of coronary calcium. An additional 0.5-mm CTA data set, with 0.25-mm increments, that is used for CTA evaluation in clinical practice was reconstructed. The reconstructions were transferred to a workstation for analysis.

Analysis

Analysis of coronary artery calcium was performed on a postprocessing workstation (Vitrea FX, version 1.0, Vital Images) using dedicated CT calcium score analysis software (VScore, Vital Images). Coronary calcium was defined as an area of at least three “face-connected” voxels in the axial plane in the course of a coronary artery, with an attenuation threshold value of 130 HU or greater. Three in-axial-plane face-connected voxels correspond to a minimum lesion area greater than 1 mm2, which is used as a reference value in calcium scoring [6]. Calcium scores of each investigation were calculated and expressed as Agatston scores for standard of reference CT calcium score and for CTA reconstructions.

Contour drawing was performed by two investigators with 2 years (observer 1) and 4 years (observer 2) of experience in cardiac CT; observer 1 was supervised by a radiologist with 7 years of experience in cardiac CT. Observers were aware that patients had been selected on the basis of the presence (n = 50) or absence (n = 50) of coronary calcium but were not aware of medical history of individual patients. Examinations were presented in random order. For CTA, calcifications that were visually identified in the course of the coronary arteries were marked by the investigator. The investigator was allowed to compare the 3.0-mm CTA data set with the 0.5-mm CTA data set. Marking was done on the 3.0-mm data set by precise contour drawing of visually identified calcium spots after zooming in on the focus, allowing visual identification of individual pixels. Automatic recognition of pixels of 130 HU or greater was switched off because the design of the coronary calcium analysis program is dedicated for unenhanced CT. After manual contour drawing, calcium scores were automatically calculated on the basis of the 130 HU threshold value. After obtaining the calcium scores in the CTA data sets of all patients, the calcium scores were obtained in CT calcium score data sets. With automatic recognition of 130 HU or more, pixels exceeding this threshold value are colored purple by the postprocessing tool. In each slice (depending on scan range, 47 or 53 slices), these areas were manually encircled when present in the course of each coronary artery. Calcium scores were automatically calculated. A time interval of at least 2 weeks between scoring the CTA and the CT calcium score was used to prevent recognition bias. Patients were classified according to Agatston risk groups as defined by Rumberger et al. [27]. Although this risk stratification scheme is based on absolute Agatston scores and does not account for patient age, sex, and race, recent studies have shown that absolute calcium scores may predict cardiovascular events better than adjusted percentiles [28, 29].

figure
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Fig. 1 57-year-old man with coronary artery calcifications. A and B, CT calcium score images show coronary artery calcifications (arrows) in left anterior descending coronary artery. CT calcium score was calculated with automatic recognition of ≥ 130 HU switched off (A) and automatic recognition switched on (purple color, B). Agatston calcium score calculated by CT calcium score was 151. C and D, Coronary artery calcifications (arrows) in left anterior descending coronary artery are seen on CT coronary angiography (CTA) images with 3.0 mm (C) and 0.5 mm (D) reconstruction. Agatston calcium score was 96 with 3.0 mm CTA reconstruction (C). Comparison with 0.5 mm CTA reconstruction that is used in clinical practice for coronary artery lumen evaluation was allowed (D).

Statistical Analysis

Statistical analysis was performed using SPSS for Windows (version 16.0, SPSS). The diagnostic performance of CTA in the detection of coronary artery calcium is presented as sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy; CT calcium score was used as the standard of reference. The mean and median calcium scores and SDs were calculated for CT calcium score and for CTA for the whole group and for the Agatston risk groups [27]. The Wilcoxon's signed rank test for two related samples was applied to determine a statistically significant difference between the calcium scores obtained with CT calcium score and CTA. The intraclass correlation coefficient (ICC) was calculated to evaluate method agreement between CT calcium score and CTA investigations and to assess interobserver agreement. An ICC less than 0.4 indicated poor reproducibility, an ICC of 0.4–0.75 indicated fair to good reproducibility, and an ICC greater than 0.75 indicated excellent reproducibility [30]. The method described by Bland and Altman [31] was used to study limits of agreement and systematic error between the two methods and between the two observers, respectively. A p value of less than 0.05 was considered statistically significant.

Results
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Positive Calcium Score (≥ 1)

For observer 1, the mean calcium score of the 50 patients with a positive CT calcium score was 254 ± 501 (median, 82). At CTA, coronary calcium was detected in 43 (86%) of 50 patients, with a mean calcium score of 102 ± 202 (median, 40). Seven patients had a false-negative calcium score at CTA, with scores of 1 (n = 4 patients), 2 (n = 1 patient), 4 (n = 1 patient), and 8 (n = 1 patient). Figure 1 shows a comparison of coronary artery calcium visualization with CT calcium score and CTA.

For observer 2, the mean calcium score of the 50 patients with a positive CT calcium score was 272 ± 531 (median, 82). Coronary artery calcium was detected in 46 (92%) of these 50 patients at CTA, with a mean calcium score of 94 ± 147 (median, 45). Four patients had a false-negative calcium score, with scores of 1 (n = 2 patients) and 8 (n = 2 patients).

The distribution of patients within different Agatston risk groups, as defined by Rumberger et al. [27], is shown in Table 1. No statistically significant difference was found between CT calcium score and CTA-derived calcium scores for patients with low calcium scores (< 10, both observers). For the patients with calcium scores exceeding 10 (observer 2) and 100 (observer 1), the calcium score was statistically significantly underestimated by CTA, with a mean factor of 2.8 (observer 1 range, 2.4–4.1; observer 2 range, 1.7–4.5) compared with the reference method (Table 1).

TABLE 1: CT Calcium Score and Agatston Score Risk Group Distribution

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Fig. 2 Bland-Altman analysis showing limits of agreement and systematic errors for both observers. Results for Agatston calcium scores obtained with CT calcium score (CTCS) and CT angiography (CTA) are shown for observer 1 (A) and for observer 2 (B). Dashed lines show upper and lower limits of agreement ± 1.96 SD and 95% CI. Note that good agreement can be observed for low calcium scores, whereas highest Agatston scores above upper limit of calcium score exceeding 544 (observer 1) and 686 (observer 2) contain systematic error.

Despite underestimated calcium scores by CTA, good ICCs (observer 1, 0.78; observer 2, 0.62) were found between CT calcium score and CTA-derived calcium scores, showing good-to-excellent agreement between the two methods for the whole patient group (both p < 0.01). Bland-Altman plots in Figure 2 show the limits of agreement and systematic error for individual scores and show good agreement for low calcium scores, whereas the highest scores (exceeding 466 for observer 1 and 596 for observer 2; for the highest risk Agatston group, > 400) show systematic error resulting from underestimation of CTAderived calcium scores.

Zero Calcium Score (0)

For observer 1, 49 (98%) of the 50 patients with a zero CT calcium score had a zero score derived from CTA as well. In one patient, a calcium score of 5 was calculated. In that patient, contrast enhancement in the left anterior descending artery was visually interpreted as coronary calcium. All 50 patients with a zero CT calcium score scored by observer 2 had a zero CTA-derived calcium score as well.

Diagnostic Performance for Detecting Coronary Artery Calcium

For observer 1, the diagnostic performance and predictive value of CTA for the detection of coronary artery calcium were as follows: sensitivity, 86% (95% CI, 73–94%); specificity, 98% (95% CI, 88–100%); positive predictive value, 98% (95% CI, 86–100%); negative predictive value, 88% (95% CI, 75–94%); and diagnostic accuracy, 92%. For observer 2, the values were as follows: sensitivity, 92% (95% CI, 80–97%); specificity, 100% (95% CI, 91–100%); positive predictive value, 100% (95% CI, 90–100%); negative predictive value, 93% (95% CI, 81–98%); and diagnostic accuracy, 96%.

The change in classification according to risk groups for the whole patient population for CTA-derived Agatston scores, compared with the standard of reference CT calcium score, for the two observers is shown in Table 2. Classification in another risk group occurred for 27% of patients by using CTA-derived calcium scores; for observer 1, “downgrading” of the Agatston risk group occurred in 23% of cases, and “upgrading” of Agatston risk group occurred in 4% of cases. For observer 2, classification in another risk group occurred for 20% of patients by using CTA-derived calcium scores, whereas downgrading of the Agatston risk group occurred in 19% of cases, and upgrading of Agatston risk group occurred in 1% of cases.

TABLE 2: Shift in Risk Group Distribution for CT Calcium Score and CT Angiography–Derived Agatston Scores

Interobserver Variability

Interobserver agreement was excellent for both the CT calcium score–Agatston scores (ICC, 0.997; p < 0.001) as well as the CTA-derived Agatston scores (ICC, 0.94; p < 0.001) for the total group. Also, for the groups with a positive CT calcium score–Agatston score, excellent interobserver agreement was found (ICC for CT calcium score, 0.996; ICC for CTA, 0.93; both p < 0.001). Bland-Altman plots in Figure 3 show levels of agreement and systematic error for individual scores and show excellent observer agreement. In the highest risk group, a few outliers for CT calcium score–Agatston scores were found between the two observers. The differences in Agatston scores between the two observers for these outliers can be explained by dissimilar inclusion of coronary artery calcium at the origin of the coronary arteries that was continuous with calcifications in the aortic wall.

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Fig. 3 Bland-Altman analysis showing interobserver agreement, limits of agreement, and systematic errors for Agatston calcium score calculated by both CT calcium score (CTCS) (A) and CT angiography (CTA) (B). Dashed lines show upper and lower limits of agreement ± 1.96 SD and 95% CI. Excellent agreement can be observed for both CTCS as well as CTA-derived calcium scores between two observers (p < 0.001).

Discussion
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The main finding of the current study is that the presence of coronary calcification can be estimated by using contrast-enhanced CTA, with excellent diagnostic accuracy, positive predictive value, and specificity. Second, the Agatston score derived from coronary CTA correlates well with unenhanced CT calcium score, which is the standard of reference. Third, both enhanced and unenhanced CT provide equivalent Agatston scores when there is a limited amount of coronary calcium, but coronary CTA underestimates the amount of calcium in cases with higher Agatston scores. Fourth, deriving Agatston scores from coronary CTA can be obtained with a high reproducibility and excellent observer agreement.

The excellent diagnostic accuracy, positive predictive value, and specificity found in the current study indicate that coronary calcium can be considered as present with a positive CTA-derived Agatston score. Although a good sensitivity and negative predictive value were found, the absence of coronary calcium on CTA may be a false-negative observation of coronary calcium that is actually present. However, no large amounts of coronary calcium were missed on CTA, because in missed cases, the actual Agatston score was low, and within Agatston risk group 10 or less, the median Agatston score was 2.

In two previous studies in which Agatston scores were derived from CTA investigations, the detection threshold for coronary calcium was increased from 130 to 350 HU for CTA-derived calcium scores and was compared with the 130 HU CT calcium score threshold [22, 23]. One study, which used nonoverlapping 3.0-mm-slice CT calcium score to compare with overlapping 1.25-mm-slice CTA in 50 patients, reported an overestimation of CTA Agatston scores by a factor of approximately 3 [23]. It is unclear whether the overestimation found in that study was due to the inclusion of contrast material exceeding 350 HU or to differences in reconstructed slice thickness and use of overlapping image reconstruction. With thin-slice overlapping images, voxel sizes and, thus, partial volume effect decrease. The chance of a voxel containing sufficient calcification attenuation to reach the detection threshold increases with smaller voxels [32], leading to higher scoring results [25, 33, 34].

Another study used 3.0-mm slices and 2.0-mm increments for both CTA and CT calcium score [22]. In that study, CTA data for only 28 of 38 patients were used for analysis, because seven patients with a negative CT calcium score were not included for CTA analysis, and CTA analysis could not be performed for another three patients. CTA Agatston scores were underestimated by a factor of approximately 3 [22], which is the range of the current study. In the current study, the traditional threshold value of 130 HU was used for both CTA-derived calcium scores and CT calcium score. Good agreement was found between CT calcium score and CTA-derived calcium scores. Although low Agatston scores derived from CTA were not statistically different from the CT calcium score, a substantial underestimation was found in the higher risk groups, which led to a downshift of risk group for 20–22% of the patients, whereby 1–4% of patients shifted from the high-risk group (calcium score, > 400) to the intermediate-risk group (calcium score, 100–400). Total shift in risk groups occurred for 20–27% of all our patients by visual assessment of coronary artery calcium and by using the 130 HU threshold value, compared with 57% of analyzed patients in a study that used automatic assessment and 350 HU as threshold value for detection [23].

Furthermore, in the current study, all 100 CTA studies were included for analysis. Moreover, by using volumetric imaging within a single heartbeat for both the CT calcium score and CTA acquisitions, the 3D volume data sets reconstructed to 3.0-mm slices were technically most comparable. It should be noted that the original Agatston score and large outcome studies were based on nonoverlapping 3.0-mm-slice data sets as well [3, 10]. In symptomatic patients, the extent of coronary artery calcium has been shown to provide additional prognostic information over invasive coronary angiography alone [6]. However, even a zero calcium score may not exclude obstructive coronary artery disease [1114], and a positive score is no direct indicator for coronary artery stenosis. Therefore, CT calcium score alone seems not to be optimal for excluding coronary artery disease in symptomatic patients and is often followed by CTA.

Now that the CTA technique has developed into a clinical tool that is increasingly used for coronary artery evaluation in routine clinical practice, CTA rather than CT calcium score may be used for coronary artery evaluation. CTA allows direct evaluation of the presence and extent of coronary artery luminal obstruction, whereas CTA-based estimation of the presence and extent of coronary artery calcium from the same images may provide additional risk information that may obviate the traditional CT calcium score. Radiation exposure is of major concern in coronary CTA because of the associated risk of radiation-induced cancer [35]. Several methods, including prospective ECG-triggering techniques, have been developed and have been very effective in reducing patient dose [36, 37]. If a separate CT calcium score examination can be avoided by using the CTA examination in deriving the presence and extent of coronary calcium, this may aid substantially in further decreasing patient dose.

The present study has some limitations. Deriving Agatston scores from CTA was more time consuming than deriving Agatston scores from CT calcium scores (the standard of reference), with approximately double the time needed for analysis, because the reader was not alerted by automatic color encoding of coronary artery calcium during evaluation. Also, the scoring method used may not be available on all workstations and may be vendor dependent. Application of the technique in routine clinical practice may require software improvements. Further coronary artery analysis software developments may facilitate deriving calcium scores from CTA investigations. Furthermore, although good method agreement between CT calcium score and CTA-derived calcium scores was found, it is unclear whether the CTA-derived Agatston scores may be used for actual risk stratification—even if a conversion factor is applied—as is done now for the large patient databases obtained by electron beam CT [9, 10].

A relatively small group of 100 patients was used for analysis in this feasibility study, and patients were selected according to the presence or absence of coronary calcium (n = 50 patients each). It is not known what the effect of using CTA-derived calcium scores by means of risk stratification and clinical consequences would be for individual patients, because such studies would require large study populations other than our selected groups of 50 patients each, because outcome depends on disease prevalence. It should be noted that patient risk stratification is not based on the amount of coronary artery calcium alone but also depends on patient characteristics and the presence or absence of other risk factors [2]. It has been shown that using CTA data, with its information on luminal narrowing and plaque composition, has incremental prognostic value over using CT calcium score alone [14, 18, 38]. Therefore, combining the results of luminal narrowing, plaque composition, and calcium score may provide optimal information for CT-based risk stratification. Radiation dose was relatively high, because the study was performed early after installation of the new scanner type. At that time, the majority of patients (68%) had undergone imaging that included a functional analysis with a relatively high radiation dose compared with prospective CTA for coronary imaging alone that is routinely applied today. Also, tube current settings for CT calcium score have now been substantially decreased.

In conclusion, coronary artery calcium can be detected on CTA with high accuracy. The Agatston calcium score derived from CTA shows good correlation with unenhanced CT calcium score and is highly reproducible. However, higher Agatston scores are systematically underestimated when derived from CTA.

Address correspondence to L. J. M. Kroft ().

We thank B. J. A. Mertens for statistical advice.

References
Previous sectionNext section
1. Oudkerk M, Stillman AE, Halliburton SS, et al. Coronary artery calcium screening: current status and recommendations from the European Society of Cardiac Radiology and North American Society for Cardiovascular Imaging. Int J Cardiovasc Imaging 2008; 24:645–671 [Google Scholar]
2. Greenland P, Bonow RO, Brundage BH, et al. ACCF/AHA 2007 clinical expert consensus document on coronary artery calcium scoring by computed tomography in global cardiovascular risk assessment and in evaluation of patients with chest pain: a report of the American College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography). Circulation 2007; 115:402–426 [Google Scholar]
3. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 1990; 15:827–832 [Google Scholar]
4. Callister TQ, Cooil B, Raya SP, Lippolis NJ, Russo DJ, Raggi P. Coronary artery disease: improved reproducibility of calcium scoring with an electron-beam CT volumetric method. Radiology 1998; 208:807 –814 [Google Scholar]
5. Hoffmann U, Siebert U, Bull-Stewart A, et al. Evidence for lower variability of coronary artery calcium mineral mass measurements by multidetector computed tomography in a community-based cohort—consequences for progression studies. Eur J Radiol 2006; 57:396 –402 [Google Scholar]
6. Keelan PC, Bielak LF, Ashai K, et al. Long-term prognostic value of coronary calcification detected by electron-beam computed tomography in patients undergoing coronary angiography. Circulation 2001; 104:412 –417 [Google Scholar]
7. Wong ND, Hsu JC, Detrano RC, Diamond G, Eisenberg H, Gardin JM. Coronary artery calcium evaluation by electron beam computed tomography and its relation to new cardiovascular events. Am J Cardiol 2000; 86:495 –498 [Google Scholar]
8. Arad Y, Spadaro LA, Goodman K, Newstein D, Guerci AD. Prediction of coronary events with electron beam computed tomography. J Am Coll Cardiol 2000; 36:1253 –1260 [Google Scholar]
9. Shaw LJ, Raggi P, Schisterman E, Berman DS, Callister TQ. Prognostic value of cardiac risk factors and coronary artery calcium screening for all-cause mortality. Radiology 2003; 228:826–833 [Google Scholar]
10. Budoff MJ, Shaw LJ, Liu ST, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. J Am Coll Cardiol 2007; 49:1860 –1870 [Google Scholar]
11. Cheng VY, Lepor NE, Madyoon H, Eshaghian S, Naraghi AL, Shah PK. Presence and severity of noncalcified coronary plaque on 64-slice computed tomographic coronary angiography in patients with zero and low coronary artery calcium. Am J Cardiol 2007; 99:1183 –1186 [Google Scholar]
12. Akram K, O'Donnell RE, King S, Superko HR, Agatston A, Voros S. Influence of symptomatic status on the prevalence of obstructive coronary artery disease in patients with zero calcium score. Atherosclerosis 2009; 203:533–537 [Google Scholar]
13. Rubinshtein R, Gaspar T, Halon DA, Goldstein J, Peled N, Lewis BS. Prevalence and extent of obstructive coronary artery disease in patients with zero or low calcium score undergoing 64-slice cardiac multidetector computed tomography for evaluation of a chest pain syndrome. Am J Cardiol 2007; 99:472 –475 [Google Scholar]
14. van Werkhoven JM, Schuijf JD, Gaemperli O, et al. Incremental prognostic value of multi-slice computed tomography coronary angiography over coronary artery calcium scoring in patients with suspected coronary artery disease. Eur Heart J 2009; 30:2622 –2629 [Google Scholar]
15. Mowatt G, Cook JA, Hillis GS, et al. 64-Slice computed tomography angiography in the diagnosis and assessment of coronary artery disease: systematic review and meta-analysis. Heart 2008; 94:1386 –1393 [Google Scholar]
16. Miller JM, Rochitte CE, Dewey M, et al. Diagnostic performance of coronary angiography by 64-row CT. N Engl J Med 2008; 359:2324 –2336 [Google Scholar]
17. Meijer AB, YL O, Geleijns J, Kroft LJ. Metaanalysis of 40- and 64-MDCT angiography for assessing coronary artery stenosis. AJR 2008; 191:1667 –1675 [Abstract] [Google Scholar]
18. Ostrom MP, Gopal A, Ahmadi N, et al. Mortality incidence and the severity of coronary atherosclerosis assessed by computed tomography angiography. J Am Coll Cardiol 2008; 52:1335 –1343 [Google Scholar]
19. Min JK, Shaw LJ, Devereux RB, et al. Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. J Am Coll Cardiol 2007; 50:1161 –1170 [Google Scholar]
20. Hadamitzky M, Freissmuth B, Meyer T, et al. Prognostic value of coronary computed tomographic angiography for prediction of cardiac events in patients with suspected coronary artery disease. JACC Cardiovasc Imaging 2009; 2:404 –411 [Google Scholar]
21. Budoff MJ, Achenbach S, Blumenthal RS, et al. Assessment of coronary artery disease by cardiac computed tomography: a scientific statement from the American Heart Association Committee on Cardiovascular Imaging and Intervention, Council on Cardiovascular Radiology and Intervention, and Committee on Cardiac Imaging, Council on Clinical Cardiology. Circulation 2006; 114:1761 –1791 [Google Scholar]
22. Muhlenbruch G, Wildberger JE, Koos R, et al. Coronary calcium scoring using 16-row multislice computed tomography: nonenhanced versus contrast-enhanced studies in vitro and in vivo. Invest Radiol 2005; 40:148 –154 [Google Scholar]
23. Hong C, Becker CR, Schoepf UJ, Ohnesorge B, Bruening R, Reiser MF. Coronary artery calcium: absolute quantification in nonenhanced and contrast-enhanced multi-detector row CT studies. Radiology 2002; 223:474–480 [Google Scholar]
24. Glodny B, Helmel B, Trieb T, et al. A method for calcium quantification by means of CT coronary angiography using 64-multidetector CT: very high correlation with Agatston and volume scores. Eur Radiol 2009; 19:1661 –1668 [Google Scholar]
25. Muhlenbruch G, Klotz E, Wildberger JE, et al. The accuracy of 1- and 3-mm slices in coronary calcium scoring using multi-slice CT in vitro and in vivo. Eur Radiol 2007; 17:321–329 [Google Scholar]
26. Menzel HG, Schibilla H, Teunen D, et al. European guidelines on quality criteria for computed tomography: report no. EUR 16262 EN. Luxembourg: European Commission,2000 . [Google Scholar]
27. Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc 1999; 74:243 –252 [Google Scholar]
28. Budoff MJ, Nasir K, McClelland RL, et al. Coronary calcium predicts events better with absolute calcium scores than age-sex-race/ethnicity percentiles: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol 2009; 53:345 –352 [Google Scholar]
29. Akram K, Voros S. Absolute coronary artery calcium scores are superior to MESA percentile rank in predicting obstructive coronary artery disease. Int J Cardiovasc Imaging 2008; 24:743–749 [Google Scholar]
30. Rosner B. Multisample inference. Fundamentals of biostatistics, 5th ed. Belmont: Duxbury Press, 2000:563 [Google Scholar]
31. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1:307 –310 [Google Scholar]
32. Muhlenbruch G, Thomas C, Wildberger JE, et al. Effect of varying slice thickness on coronary calcium scoring with multislice computed tomography in vitro and in vivo. Invest Radiol 2005; 40:695 –699 [Google Scholar]
33. Sabour S, Rutten A, van der Schouw YT, et al. Inter-scan reproducibility of coronary calcium measurement using multi detector-row computed tomography (MDCT). Eur J Epidemiol 2007; 22:235 –243 [Google Scholar]
34. Groen JM, Greuter MJ, Schmidt B, Suess C, Vliegenthart R, Oudkerk M. The influence of heart rate, slice thickness, and calcification density on calcium scores using 64-slice multidetector computed tomography: a systematic phantom study. Invest Radiol 2007; 42:848–855 [Google Scholar]
35. Einstein AJ, Henzlova MJ, Rajagopalan S. Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography. JAMA 2007; 298:317–323 [Google Scholar]
36. Earls JP, Berman EL, Urban BA, et al. Prospectively gated transverse coronary CT angiography versus retrospectively gated helical technique: improved image quality and reduced radiation dose. Radiology 2008; 246:742–753 [Google Scholar]
37. Efstathopoulos EP, Kelekis NL, Pantos I, et al. Reduction of the estimated radiation dose and associated patient risk with prospective ECG-gated 256-slice CT coronary angiography. Phys Med Biol 2009; 54:5209 –5222 [Google Scholar]
38. Rubinshtein R, Halon DA, Gaspar T, Peled N, Lewis BS. Cardiac computed tomographic angiography for risk stratification and prediction of late cardiovascular outcome events in patients with a chest pain syndrome. Int J Cardiol 2009; 137:108–115 [Google Scholar]

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