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Calcium Scoring of the Coronary Artery by Electron Beam CT

How to Apply an Individual Attenuation Threshold

¹ Tulane University School of Medicine, Cardiology Section, SL48, 1430 Tulane Ave., New Orleans, LA 70112.
² EBT Research Foundation, 353 New Shackle Island Rd., Hendersonville, TN 37025.
³ Owen Graduate School of Management, Vanderbilt University, 401 21st Ave. S. Nashville, TN 37203.

Received June 13, 2001; accepted after revision August 27, 2001.

 
Presented at the annual meeting of the Radiological Society of North America, Chicago, November 1999.

Address correspondence to P. Raggi.

Abstract

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OBJECTIVE. Our aim was to assess the inter- and intraindividual variability of the attenuation threshold used to identify coronary artery calcification on electron beam CT and to illustrate a new threshold method.

MATERIALS AND METHODS. We measured the soft-tissue attenuation of regions surrounding the coronary arteries at the level of the left main coronary artery ostium (high level) and at the bottom of the heart (low level) in 48 consecutive patients (22 men, 26 women). Mean ± 2 standard deviations (SD) of soft-tissue attenuation and variance of soft-tissue density and SDs were calculated at each level for every patient. It was assumed that setting an attenuation threshold greater than or equal to 3 SDs above that of soft tissue at each myocardial level would eliminate 99.5% of all scatter artifacts, allowing precise identification of calcific deposits.

RESULTS. For the entire patient cohort, the average soft-tissue attenuation was 41 H and 35 H at the high and low levels, respectively (p < 0.01), indicating a large intraindividual variability. The SDs of soft-tissue attenuation measured by the computer software at the high and low levels were not different (26 H at the high level and 28 H at the low level; p = not significant). However, the calculated SD of the individual mean soft-tissue attenuation was 5 H at the high level and 8 H at the low level, again indicating a large intraindividual variability (p < 0.01). The addition of 3 measured SDs above the mean individual soft-tissue attenuation predicted a mean threshold of 120 and 121 H at the high and low levels, respectively, but with a wide interindividual variability (83-193 H at the high level and 79-242 H at the low level). There was a strong correlation between body weight and SD of soft-tissue attenuation at the low level (r = 0.75, p < 0.001) and a weaker but statistically significant correlation between weight and SD of soft-tissue attenuation at the high level (r = 0.51, p < 0.001).

CONCLUSION. For the patients in this study, a threshold of 120 H for the detection of coronary calcification by electron beam CT seemed more appropriate than a threshold of 130 H, which is currently in use. However, given the great inter- and intraindividual variability, a biologic threshold tailored to the individual patient and to each individual imaging level should be used instead of a fixed threshold.

Introduction

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Coronary atherosclerosis can be detected in its preclinical stages by means of CT imaging to visualize coronary artery calcification [1,2,3,4,5,6,7]. Traditionally, this form of imaging has been performed with electron beam CT, although recently multislice helical CT scanners have been introduced for similar applications. The extent of vascular calcification is usually quantitated by means of the score introduced by Agatston et al. [8]. Both this score and a more recently introduced volumetric method, with better reproducibility than that of the conventional score [9], use a fixed minimum attenuation threshold of 130 H for differentiation of noncalcified and calcified arterial lesions. The selection of this CT number was based on the speculative assumption that most noncalcified areas would be excluded from computation if the attenuation threshold were kept approximately three times above soft-tissue attenuation. The inherent variability of biologic systems, however, seems in contrast with the rigid applicability of such a universal attenuation threshold. Furthermore, imaging with electron beam CT often produces substantial radiation scatter. This generates image noise and interpretative difficulties, especially in the proximity of the diaphragm where radiation scatter is more pronounced. Imaging with CT is also affected by several other factors, such as the size and geometry of the object imaged, the brand and model of the CT scanner used, and the size of the field of view used [10]. Therefore, given the substantial variability that can occur in CT number calculation, a fixed threshold of 130 H for all patients is likely to be inadequate. In this study, we tried to assess the degree of inter- and intraindividual variability in soft-tissue attenuation and to identify the ideal attenuation threshold for an individual patient. Forty-eight randomly selected patients were the subjects of our study.

Materials and Methods

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Patient Selection and Imaging Procedures
The study was conducted according to standard ethical criteria for clinical research and was approved by our internal review board, and all individuals signed an informed consent form before undergoing imaging. We enrolled 48 subjects (22 men, 26 women) referred by primary care physicians for electron beam CT screening for coronary artery calcification. Patients underwent imaging with a C-100 scanner (Imatron, South San Francisco, CA). Imaging was performed using a 100 msec scan time and a 3-mm single slice thickness, with a total of 36-40 slices obtained during two breath-holding periods. Scanning was electrocardiographically triggered at 60% of the R-Rwave interval. Images were obtained with a 30-cm² field of view (pixel size, 0.586 mm), and a sharp reconstruction kernel was used. Scans showing motion artifacts or artifacts produced by erroneous ECG gating were excluded from the study. Image analysis was performed by a sole physician expert in electron beam CT to guarantee consistency of the methodology. The investigator used a NetraMD workstation (ScImage, Los Altos, CA) equipped with a calculation package, calipers, and a densitometry tool. Body weight was obtained for all patients, and the thickness of the subcutaneous fat pad was measured in the abdominal wall at the level of the last tomographic cut near the diaphragm (measurements expressed in millimeters).

Measurements and Statistical Analysis
The attenuation of uniform areas of soft tissue in the immediate vicinity of the coronary arteries was measured at the level of the ostium of the left main coronary artery (considered the high level) and the level of the most caudad image still containing portions of the coronary vessels (considered the low level). Mean and standard deviation (SD) of soft-tissue attenuation were measured at the high level and the low level for all patients. Optimal individual thresholds were then estimated by adding 3 SDs above the mean soft-tissue attenuation at each level. This approach is justifiable on the basis of the bell shape distribution of CT numbers found in soft tissue and blood pools. The calculation of the optimal individual attenuation threshold was performed using a semiautomatic software (ScImage). This approach requires the operator to identify two or three areas of interest in the soft tissue near the coronary arteries. Therefore, the software calculates the best threshold by adding 3 SDs to the mean soft-tissue attenuation (Fig. 1A,1B). The process takes an average of 10-15 sec to complete.

View larger version (135K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1A. —Axial electron beam CT scans of chest obtained in 74-year-old woman at level of proximal to middle portion of left anterior descending coronary artery show calcification. Computer software automatically highlights all pixels, with CT number > 130 H in yellow. Along with calcification of left anterior descending coronary artery (in white rectangle), substantial image noise (scattered yellow pixels) is also seen.

View larger version (125K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1B. —Axial electron beam CT scans of chest obtained in 74-year-old woman at level of proximal to middle portion of left anterior descending coronary artery show calcification. Computer software automatically highlights all pixels, with CT number > 130 H in yellow. After calculation of optimal attenuation threshold by adding 3 standard deviations (SD) to measured mean soft-tissue CT number, background noise disappears. In this example, mean soft-tissue CT number is 45 H with SD of 40 H, and calculated optimal threshold is 165 H.

The variance of soft-tissue attenuation measurements and their related SDs were calculated to gauge the extent of interindividual variability. The paired t test was used to assess statistical differences between an individual patient's mean and SD at the high and low levels. The F test was chosen to evaluate whether the SDs and variances of various arrays were significantly different, and the Pearson's correlation coefficient was used to assess the linear relationship between body weight and attenuation variance. Multiple regression was used to study the relationship between an individual mean attenuation (at high and low levels) and the patient's sex, weight, and abdominal fat pad thickness.

A p value of < 0.05 was chosen as statistically significant. All reported statistical values are two-sided.

Results

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We studied 22 men and 26 women. The mean ± 2 SDs of body weight for men was 208 ± 35 lbs and 185 ± 47 lbs for women. For the entire group, the mean soft-tissue attenuation measured at the high and low levels were 41 H and 35 H, respectively (p < 0.01), indicating substantial intraindividual variability. The calculated SDs of the measured individual soft-tissue attenuation at the high level and the low level were also statistically different (5 H versus 8 H, respectively; p < 0.01), again indicating substantial intraindividual variability. The average of the SDs of the soft-tissue CT number (measured by the computer software) at the high and low levels was 26 H and 28 H, respectively (p = not significant). Figures 2 and 3 show the distribution of individual mean soft-tissue attenuation and the individual SDs at both the high and low levels. The box plots show a wide range of values for both imaging levels and for both types of measurement. At each level, we calculated the optimal individual threshold as the mean individual attenuation plus 3 individual SDs. Across patients, the mean optimal thresholds were 120 H and 121 H for the high and low levels, respectively. Nonetheless, there was a wide interindividual variability (range of thresholds, 83-193 H for the high level; range of thresholds, 79-242 H for the low level).

View larger version (13K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 2. —Box plots of mean soft-tissue attenuation measured at level of origin of left main coronary artery (high-level mean) and at level of diaphragm (low-level mean).

View larger version (12K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 3. —Box plots of standard deviation (SD) of soft-tissue attenuation measured at level of origin of left main coronary artery (high-level SD) and at level of diaphragm (low-level SD).

Notably, body weight seemed to have a substantial influence on the variability of the soft-tissue measurements. Figure 4 shows the correlation existing between soft-tissue attenuation measurements made at the low level and body weight in all 48 patients. As the body weight increases, the mean soft-tissue CT number decreases, and the SD increases. We further noticed a statistically significant correlation between body weight and SD of soft-tissue attenuation at the low level (Pearson's correlation coefficient, r = 0.75, p < 0.001). There was a weaker but still statistically significant correlation between weight and SD of soft-tissue attenuation at the high level (r = 0.51, p < 0.001). This observation indicates that the larger the body weight, the wider the range of soft-tissue CT numbers that can be measured and the more appropriate the use of an individually tailored attenuation threshold. Figure 5 shows the relationship between patient body weight and estimated optimal attenuation threshold at the low level. As the body weight increases, the estimated optimal threshold increases, reflecting the direct relationship existing between body weight and SD of soft-tissue attenuation measurements. Similar conclusions were reached for estimates made at the high level (data not shown).

View larger version (11K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 4. —Correlation between soft-tissue attenuation measurements made at bottom of heart (low level) and body weight in all 48 patients. As body weight increases, mean soft-tissue attenuation decreases and standard deviation increases.

View larger version (12K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 5. —Correlation between ideal threshold (mean soft-tissue CT number plus 3 standard deviations [SD]) at bottom of heart (low level) and patient's body weight. As body weight increases, ideal soft-tissue attenuation increases as function of increasing SD (y = 0.4839x + 26.179).

Finally, there was a linear relationship between a patient's ideal calcium threshold at the low level, the individual's body weight, and the abdominal fat pad thickness as expressed by the following regression equation: mean + 3 SDs (low level) = 29 + 0.365 weight + 1.07 x (fat pad thickness). The coefficients of weight and abdominal fat were both significant (p < 0.001 and p = 0.013, respectively), and the multiple regression explained 48% of the variance in the optimal threshold at the low level. When the variable sex was added to this model, it was only marginally significant (p = 0.051). The ideal threshold at the high level did not show a multivariate relationship between weight and abdominal fat, and the coefficient of weight was not significantly nonzero (p = 0.15).

Discussion

Top Abstract Introduction Materials and Methods Results Discussion References

 
In the current study, we sought to estimate the optimal attenuation threshold for detection of coronary calcification on electron beam CT. We assumed that setting a threshold 3 SDs above mean soft-tissue attenuation would eliminate 99.5% of the artifacts. We observed that in the patient cohort, a threshold of 120 H was on average more accurate than the currently used level of 130 H. More importantly, we noted a substantial inter-and intraindividual variability that argued for the benefit of using an individually tailored threshold.

The current study suggests a close correlation between CT number variability and body weight, especially at the bottom of the heart where the interaction of abdominal fat pad and liver dome increases image noise substantially. This renders the quantification of coronary calcium detected in the middle to distal portions of the coronary arteries less accurate. Body weight may be responsible for increased variability because of several mechanisms. First, a larger weight is usually associated with a larger body surface, and this often requires the use of a larger field of view with a larger pixel size. The size of the reconstructed pixel is a known factor that influences overall image quality [11]. In fact, as the pixel size increases, the number of photons detected per pixel increases, with improved signal-to-noise ratio. However, expansion of the pixel size will also increase partial volume, averaging with subsequent image degradation. Conversely, image degradation is to be expected with excessive reduction of the pixel size because of the reduced number of incident photons per pixel. A larger body mass may also cause image degradation because of radiation scatter: with a larger body mass, the X-ray beam must traverse a larger number of tissue interfaces with subsequent increased scatter.

Scatter is a more substantial problem with electron beam CT than with mechanical CT. In fact, electron beam CT scanners use a lower energy flux than does mechanical CT, and the gantry aperture of electron beam CT scanners is larger than that of helical CT. These two factors allow less collimation of the X-ray beams in electron beam CT than in helical CT imaging. There is, however, a U-shaped relationship between exposure time and spatial resolution [11]. The longer the exposure, therefore, the slower the imaging cycle; and the higher the photon flux per pixel, the better the spatial resolution. Although the slow imaging speed of conventional helical CT does not provide enough temporal resolution for coronary imaging, the high imaging speed of electron beam CT limits the spatial resolution of this technique compared with mechanical CT. Modern multislice CT scanners may provide a solution to this conundrum. In fact, by virtue of acquiring thinner tomographic slices, they are capable of achieving a higher spatial resolution than electron beam CT, with less partial volume averaging [12]. Also, several manufacturers have been able to increase the temporal resolution of multislice CT compared with conventional CT by adopting reconstruction algorithms that require only a portion of a 360° revolution [13, 14]. The resulting lower noise-to-image ratio should permit reduction of the threshold for detection of calcified vascular lesions compared with electron beam CT and likely increase the reproducibility of the calcium score [15, 16]. Of interest, Broderick et al. [17] show that using fast dualslice helical CT, the best calcium volume score reproducibility is obtained with the use of a threshold of 90 H.

However, two more considerations must be made. The need for an adjustable threshold on multi-slice CT, although less likely than with electron beam CT imaging, has not been investigated. Additionally, the model of the electron beam CT scanner that was used in our study (C-100; Imatron), although identical to the model used by the investigators that introduced the traditional calcium score [8], has been replaced with more recent models (C-150 and C-300; Imatron), with reportedly better resolution. In either case, electron beam CT scanners are still frequently used for coronary artery calcium screening and are currently employed for several large-scale multicenter trials. Therefore, the findings of the present analysis will be relevant to the work of several investigators.

Some of the concepts expressed in our study find indirect confirmation in the report by McCollough et al. [18]. Using electron beam CT, these investigators showed that the coronary artery calcium concentration associated with a CT number of 130 H varied greatly, both at the top and at the bottom of the heart (range, 77.1-136.4 mg/cm³ at the high level; range, 88.5-129.7 mg/cm³ at the low level), and that the variability was dependent on the image level and the patient's girth, sex, and smoking history. The authors suggested that a calibration phantom with known quantities of calcium be used before initiating an imaging session to adjust for this variability. Our suggestion on how to adjust the calcium threshold to the individual's soft-tissue attenuation at each cardiac level is born of an interest in applying CT imaging to the noninvasive follow-up of coronary atherosclerotic disease [19]. To properly accomplish this task, high calcium score reproducibility is mandatory [9]. The substantial inter- and intraindividual variability revealed by our study must be considered in association with the known variability measurable between CT scanners of different brand names and even those of the same brand names [10]. These factors may not only hamper the score reproducibility, because of changes in body habitus over time, but also the ability of a patient to transfer his or her information between different imaging centers even if the same brand name equipment is used. On the other hand, our approach of tailoring the calcium threshold to the individual patient's characteristics could likely render the follow-up of coronary calcium scores more portable and reliable.

Although our suggestions are inferential, the data strongly indicate that the rigid use of a universal attenuation threshold for all patients is inappropriate. In fact, this use can severely hamper the specificity of calcium detection and the reproducibility of calcium score calculations. Further development of computer software and careful imaging pathologic correlation studies are underway to confirm the validity of our suggestion on how to individually adjust the calcium threshold toward a more biologic value. An obvious problem that may arise from the adjustment of the CT number threshold to the individual's soft-tissue density (enhanced specificity) is the loss of information regarding less densely calcified plaque (reduced sensitivity). This aspect is therefore deserving of further investigation.

Nonetheless, we feel that the method we propose will provide a closer biologic assessment of the individual attenuation threshold necessary for the differentiation of calcium from noncalcific background scatter.

References

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