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AJR 2004; 183:103-108
© American Roentgen Ray Society

Coronary Artery Calcium Scoring Using 16-MDCT and a Retrospective ECG-Gating Reconstruction Algorithm

Jun Horiguchi1, Hideya Yamamoto2, Yuji Akiyama1, Kazushi Marukawa3, Nobuhiko Hirai1 and Katsuhide Ito3

1 Department of Radiology, School of Medicine, Hiroshima University, 1-2-3, Kasumi-cho, Minami-ku, Hiroshima 734-8551, Japan.
2 Department of Molecular and Internal Medicine, Division of Clinical Medical Science, Programs for Applied Biomedicine, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima 734-8551, Japan.
3 Department of Radiology, Division of Medical Intelligence and Informatics, Programs for Applied Biomedicine, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima 734-8551, Japan.

Received October 21, 2003; accepted after revision January 12, 2004.

 
Address correspondence to J. Horiguchi (horiguch{at}hiroshima-u.ac.jp).


Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
OBJECTIVE. Our aim was to compare detection, quantification, and cardiovascular risk stratification of coronary artery calcium (CAC) between electron beam CT and 16-MDCT with retrospective reconstruction.

SUBJECTS AND METHODS. One hundred patients underwent both electron beam CT and 16-MDCT, and coronary artery calcium score, volume, and mass were obtained.

RESULTS. Correlation between the two CT scanners was high for both calcium score (r2 = 0.955), volume (r2 = 0.952), and mass (r2 = 0.977). Although electron beam CT is viewed as the gold standard, the sensitivity and specificity in the detection of CAC using 16-MDCT with a threshold of 130 H were 98.7% and 100%, respectively. The variability of calcium scores between the two CT scanners (26.5%) was comparable with two electron beam CT scanners reported previously. The variability of calcium volume (20.7%) and mass (20.3%) was lower than that of the score (Student's t test, r = 0.05, 0.01). In clinical cardiovascular risk stratification based on two CT calcium scores, the Cohen's kappa value was 0.929. There was no significant difference between the two scanners using Wilcoxon's signed rank test (p = 0.157).

CONCLUSION. The 16-MDCT scanner with retrospective reconstruction, showing high agreement for detection and quantification of CAC with electron beam CT, holds promise in the detection of coronary artery atherosclerosis.


Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
The high cost and significant procedure-related morbidity and mortality rates associated with coronary angiography have motivated the search for a noninvasive alternative technique to assess coronary artery sclerosis [1]. Coronary artery calcification (CAC) is accepted as a predictive marker of future cardiac events. Atherosclerotic plaque progression is characterized by typical morphologic and pathologic changes as described by the American Heart Association Committee on Vascular Lesions [2]. After more than a decade of research, electron beam CT has become the standard for this area [3, 4]. However, limited availability and the relatively greater cost of electron beam CT scanners, coupled with recent advances in helical CT, have led investigators to study more widely available helical CT scanners.

Several studies applying helical CT for detection and quantification of CAC have shown a certain high degree of correlation with electron beam CT, suggesting the possibility of the assessment of coronary artery disease using helical technology. The helical CT techniques included prospectively ECG-triggered single-detector CT (with a temporal resolution of 500 msec) [5], retrospectively ECG-gated single-detector CT (500 msec) [6], prospectively ECG-triggered 4-MDCT (250 msec) [7], and retrospectively ECG-gated 4-MDCT (133–533 msec, depending on the heart rate) [8]. In contrast, a recent study using retrospectively ECG-gated single-detector CT (500 msec) has concluded that helical CT has not yet been proven to be a feasible alternative to electron beam CT for CAC quantification because of the inability to duplicate results [9].

Recently, new generation 16-MDCT scanners equipped with retrospectively ECG-gated reconstruction software for cardiac study have become available. The purpose of this study was to determine the agreement of CAC detection and quantification between electron beam CT and the 16-MDCT.


Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
The study was approved by our institutional review board, and informed consent was received from all patients involved. For 1 year, 100 consecutive subjects (73 men and 27 women; mean age ± standard deviation [SD], 62 ± 13 years; range, 41–82 years) who were asymptomatic, with no known cardiovascular disease (n = 39) or chest pain (n = 61), were included. CT was performed using an electron beam CT scanner (C-150 XL, Imatron) and a 16-MDCT scanner (LightSpeed Ultrafast 16, General Electric Medical Systems).

Electron Beam CT Protocol
The standard electron beam CT protocol was as follows; 100-msec acquisition time, 35–40 continuous gapless slices of 3-mm thickness, 130 kV, and 625 mA. The single-section mode images were obtained using ECG-triggered to 80% of the R-R interval. Image reconstruction was performed with a 512 x 512 pixel matrix using a sharp reconstruction filter. A display field of 26 cm was sufficient and yielded a pixel size of approximately 0.5 mm.

16-MDCT Protocol
Volumetric data of the entire heart were obtained in helical mode with scanning parameters of 1.25-mm collimation width x 16 detectors, a gantry rotation speed of 0.5 sec per rotation, 120 kV, and 100 mA. Pitches were variable according to the heart rate and were set according to the manufacturer's recommendations for coronary CT angiography protocol (i.e., 0.3 for 45–49 beats per minute [bpm], 0.325 for 50–59 bpm, 0.3 for 60–74 bpm, and 0.275 for > 76 bpm [where pitch was defined as table feed x rotation time / total nominal section width]). Images of 2.5-mm thickness with the center of the temporal window corresponding to 80% of the R-R interval were reconstructed with 2.5-mm spacing. In image reconstruction, single-sector, which is derived from approximately 240° of one 360° gantry rotation data, was used when the heart rate was less than 60 bpm. Multisector reconstruction was applied when the heart rate was more than 60 bpm. In this algorithm, to improve temporal resolution, we retrospectively reconstructed an image by combining some (n = 2–4) adjacent cardiac cycle data [8]. The matrix size and the field of view were the same as those for the electron beam CT protocol, and the reconstruction filter was standard.

Calcium Scoring
Calcium score, volume, and mass were determined on a commercially available external workstation (Advantage Windows, version 4.4.1, General Electric Medical Systems) using CAC-scoring software (version 3.5, Smartscore), with both electron beam CT and 16-MDCT. According to the Agatston method [3], we defined the regions of interest by vessel and slice with the threshold option for pixels greater than 130 H to measure the area and peak density of plaques. Depending on the peak density of the plaque, we multiplied an area of at least 0.52 mm2 (2 pixels) by one of the following cofactors: a factor of 1 for 130–199 H, a factor of 2 for 200–299 H, a factor of 3 for 300–399 H, and a factor of 4 for densities greater than 400 H. The total calcium score was calculated as the sum of the individual lesion scores in all coronary arteries:

where Inc is slice increment, and ST is slice thickness.

The different quantification algorithms (calcium, volume [10], and mass) were calculated using the following equations:

To avoid interobserver variability, a radiologist with 4 years' experience in CAC scored both electron beam and 16-MDCT scans. In patients with a CAC score of 0 on 16-MDCT, calcium scoring was also performed using a modified form of the Agatston method in which a threshold value for detecting calcium is set to 90 H [11].

Statistical Analysis
All values (scores and volumes) are reported as mean ± SD. For comparison of electron beam and 16-MDCT, the nonparametric Wilcoxon's signed rank test for paired data, correlation, and linear regression was used with the values derived from both CT scanners. Targeting the patient with values of nonzero on both electron beam and 16-MDCT, we calculated the percentage of variability as the means of

Variability was compared among calcium score, volume, and mass as well as between low and high heart rate subgroups. Finally, using a clinical management guideline model proposed by Rumberger et al. [12], we stratified the asymptomatic patients into one of five categories that were based on their calcium scores: very low (0), low (1–10), moderate (11–100), moderately high (101–400), and high risk (> 400). The levels of predicted risk were compared between the two scanners using the Cohen's kappa value and Wilcoxon's signed rank test.


Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
All patients could breath-hold on both electron beam and 16-MDCT. Median heart rate mean at the time of the 16-MDCT was 66 ± 10 bpm (range, 45–86 bpm; median, 64 bpm). Change in heart rate was 7 ± 9 bpm. Almost all images had a temporal resolution from 100 to 250 msec, although temporal resolution achieved by multisector reconstruction differed according to the heart rate and the number of cardiac cycles used for image reconstruction.

With the traditional 130-H threshold, the mean electron beam CT score was 390 ± 606 (range, 0–2,978; median, 112), and the mean 16-MDCT score was 404 ± 630 (range, 0–3,664; median, 101). The mean electron beam CT volume was 315 ± 470 (range, 0–2,336; median, 98), and the mean 16-MDCT volume was 321 ± 479 (range, 0–2,764; median, 105). The mean electron beam CT mass was 707 ± 1,010 (range, 0–4,355; median, 954), and the mean 16-MDCT mass was 736 ± 1,052 (range, 0–4,989; median, 825). Twenty-one persons had scores of 0 on both scans, and one person had a score of nonzero on electron beam CT and 0 on 16-MDCT (Fig. 1A, 1B). Although electron beam CT is viewed as the gold standard, 16-MDCT had a sensitivity of 98.7% and a specificity of 100%. The positive and negative predictive values were 100% and 95.5%, respectively, for 16-MDCT in this study. The relationship between the two CT scanners in calcium score, volume, and mass is shown in Figure 2A, 2B, 2C. The absolute difference and interscanner variability between the two scanners were 71 ± 115 and 26.5% in scores, 51 ± 92 and 20.7% in volumes, and 116 ± 143 and 20.3% in masses. The variability of volumes and mass was significantly less than that of the scores (Student's t test, r = 0.05, 0.01). There was no statistical difference of variability between volume and mass (Student's t test, r = 0.85). The variability was not significantly different between low (< 64 bpm, n = 39) and high (≥ 64 bpm, n = 39) heart rate groups in the scores, volumes, and masses (Student's t test, r = 0.66, 0.38, 0.93, respectively). The results of stratification of patients according to potential clinical cardiovascular risk are shown in Table 1.



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  		Fig. 1A. —78-year-old woman with atypical chest pain (heart rate, 66 beats per minute). Axial electron beam CT scan of heart shows subtle high density in right coronary artery (arrow) that is judged to be calcification. Calcium score is 1.3. Note pericardial thickening.

 


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  		Fig. 1B. —78-year-old woman with atypical chest pain (heart rate, 66 beats per minute). Axial 16-MDCT scan of heart shows that with traditional threshold of 130 H, coronary calcium is not detected. With threshold of 90 H, calcium score is calculated to be 1 on corresponding area judged as calcification on electron beam CT (A).

 


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  		Fig. 2A. —Scatterplots for electron beam CT and 16-MDCT. For coronary calcium scores, linear correlation follows equation: 16-MDCT score = 7.7 + 1.015 x electron beam CT score (r2 = 0.955). Note that calcium scores are not normally distributed.

 


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  		Fig. 2B. —Scatterplots for electron beam CT and 16-MDCT. For coronary calcium volumes, linear correlation follows equation: 16-MDCT volume = 8.85 + 0.993 x electron beam CT volume (r2 = 0.952).

 


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  		Fig. 2C. —Scatterplots for electron beam CT and 16-MDCT. For coronary calcium masses, linear correlation follows equation: 16-MDCT mass = 7.93 + 1.029 x electron beam CT mass (r2 = 0.977).

 

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  		TABLE 1 Clinical Cardiovascular Risk Stratification

 

If a threshold of 90 H was applied, 16 persons had scores of 0 on both scans, and five persons had scores of 0 on electron beam CT and nonzero on 16-MDCT. Thus, 16-MDCT had a sensitivity of 100% and a specificity of 76.2%. The positive and negative predictive values were 94.0% and 100%, respectively, for 16-MDCT.


Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
The reproducibility of CAC measurement is an important factor in the clinical value of CAC scoring. The interscanner variabilities of the CAC scores between two electron beam CT scanners are reported to range from 13% to 38% [10, 13–17]. According to the literature, the causes of interscanner variability are multifactorial, including partial volume effect [18], image noise [19], field inhomogeneity [20], lack of calibration [21], and the use of step function in the Agatston method to quantitate calcium [13]. More important, coronary artery motion artifact is considered a major contributor to CAC variability [22, 23]. For reduction or minimizing of motion artifacts of the heart, high temporal resolution levels of 19 msec [14], 41.8 msec [24], and 30–50 msec [25] are required. Low temporal resolution leads to increased artifacts manifested as black or white streaks, bands, dark spots, loss of resolution, or distortion of anatomy [26, 27]. These consequently result in either an increase or decrease in CAC scores [23].

Reported intertechnique variabilities between helical and electron beam CT are 42%, 50.2%, and 84.5% in non–ECG-gated single-detector CT (500 msec) [5, 28, 29] and 32.2% in prospectively ECG-triggered 4-MDCT (250 msec) [7]. Variability of our study is lower than that of a study using prospectively ECG-triggered 4-MDCT (250 msec) and is comparable with two electron beam CT scanners. The variability is maintained at a low level even in patients with high heart rates. This result may indicate the importance of high temporal resolution in achieving high reproducibility. Interobserver and interscanner variation of the 130-H helical CT algorithm has been shown to be as low as that of electron beam CT in one study [9], even though the result was obtained using retrospectively ECG-gated single-detector CT with a relatively low temporal resolution (500 msec).

The presence or absence of calcium is one clear-cut point that has been suggested to have clinical usefulness. The stratification of subjects according to risk and management has been based on electron beam CT data [30, 31]. If these data are applied to helical CT, equivalency in detection of CAC between electron beam and helical CT is preferable. Our study showed good results with a sensitivity of 98.7% and a specificity of 100% in the detection of CAC by helical CT with a threshold of 130 H.

Because of the MDCT scanner specification we used, the investigations of the heart should be performed with 2.5-mm instead of 3-mm slice thickness. The thinner collimation contributes to decreasing partial volume effect, thus resulting in more frequent detection of CAC [7] (Figs. 3A, 3B and 4A, 4B). In addition, since Broderick et al. [11] applied a new threshold for calcium at 90 H with helical CT and showed a good association with coronary artery disease, 90 H has been widely used for the threshold of calcium in helical CT [5–9]. In consideration of the current understanding that most frequently not calcified but lipid-rich soft plaques with a thin fibrous cap are prone to rupture, we believe that detection of subtle CAC with potential value to reduce the risk of acute coronary events is desirable [32]. However, higher sensitivities of helical CT caused by these factors inevitably lead to poor agreement in the detection of CAC between electron beam and helical CT scanners. In our study, if a threshold of 90 H was applied, specificity decreased to 76.2%, although sensitivity reached 100%.



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  		Fig. 3A. —72-year-old man with anterior chest pain (heart rate, 72 beats per minute). Axial electron beam CT scan of heart shows that no calcium is found in circumflex artery area (arrow).

 


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  		Fig. 3B. —72-year-old man with anterior chest pain (heart rate, 72 beats per minute). Axial 16-MDCT scan of heart shows high-density spot strongly suspected to indicate presence of calcium in circumflex artery (arrow); calcium score with threshold of 130 H is 2.

 


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  		Fig. 4A. —Asymptomatic 53-year-old man (heart rate, 72 beats per minute). Axial electron beam CT scan of heart shows no definite calcium in anterior descending artery area (arrow). However, calcium score is calculated as 3.

 


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  		Fig. 4B. —Asymptomatic 53-year-old man (heart rate, 72 beats per minute). Axial 16-MDCT scan of heart shows high-density spot strongly suspected to indicate calcium in anterior descending artery area (arrow); calcium score with threshold of 130 H is 6.

 

Treatment based on the CAC score is currently under debate. According to previous studies [9, 29], the difference in risk stratification of patients between electron beam and helical CT scanners was considerable, thus possibly changing how the patient is treated. In contrast, risk stratification in our study seems to be satisfactory, probably because of the relatively high levels of temporal resolution of the helical CT scanner, although further investigation is needed.

Despite our study's excellent results, we do not necessarily insist that our technique is best suited for CAC measurement using helical CT because continuous X-ray projection by helical CT, especially with a thinner collimation at a low pitch, produces excessive exposure. Using the CT dosimetry calculator offered by the ImPACT group [33], we found that effective radiation dose yielded by our protocol (CT dose index volume, 15.2–18 mGy) is more than that of the protocol recommended by the German Cardiac Society (10.6 mGy), which is three times higher than the standard electron beam CT protocol [34]. However, in our study, we used a retrospectively ECG-gated 16-MDCT protocol to test whether high temporal resolution by this method improves the variability, especially in patients with high heart rates.

Retrospective reconstruction by helical CT holds another advantage over electron beam CT. The cardiac phase in which motion artifacts are least is reported to differ considerably among coronary arteries as well as among individuals [35], thus affecting CAC score. Variability of CAC measurement caused by motion artifacts can be reduced by selecting the cardiac phase in which motion artifacts are the least on individual calcified plaques [23].

The increase in the number of detector arrays is advantageous for CAC. Breath-holding time is reduced to about 10 sec with our protocol, thus being easy to achieve. In addition, small variations in heart rate are helpful for optimizing temporal resolution on multisector reconstruction [36].

The volumetric approach has been shown to improve the reproducibility of CAC measurement both on electron beam CT [11] and on 16-MDCT [5]. According to our study, intertechnique variabilities of the CAC values between the electron beam and 16-MDCT scanners are reduced more with the volume (20.7%) and the mass (20.3%) than with the score (26.5%), with statistical significance. A combination of volumetric approach, overlapping image reconstruction, and volumetric data consisting of thin-collimation images is expected to improve reproducibility of CAC measurement. This issue, taking into consideration radiation exposure, needs to be verified by repeated scanning of a cardiac phantom.

In conclusion, the 16-MDCT scanner with multisector reconstruction, with high agreement of detection and quantification of CAC with electron beam CT, holds promise for detecting atherosclerosis and therefore may play an important role in risk assessment.


References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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