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Original Research |
1 Department of Radiology, Beijing An Zhen Hospital, Capital Medical University,
An Ding Men Wai An Zhen Li, Chao Yang District, 100029, Beijing, China.
2 Department of Ultrasound, Beijing An Zhen Hospital, Capital Medical
University, Beijing, China.
3 Department of Cardiology, Beijing An Zhen Hospital, Capital Medical
University, Beijing, China.
Received June 21, 2007;
accepted after revision September 13, 2007.
Supported in part by the Wards of Cardiology in An Zhen Hospital, Capital
Medical University.
Abstract
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MATERIALS AND METHODS. Twenty-six patients (17 men, nine women; mean age, 56 years) with suspected coronary atherosclerotic disease were studied using contrast-enhanced 64-MDCT and IVUS. The coronary arteries were divided into 10-mm segments and vascular cross-sectional area (CSA), luminal CSA, and plaque burden were measured in each segment. Plaque analysis software was used to automatically detect both plaques and vessel walls on CT images. Two investigators who were blinded to IVUS results independently determined the presence, classification, and quantitative measurement of atherosclerotic plaques on the CT images, which were then compared with the IVUS images.
RESULTS. Of 40 coronary arteries, 247 of 263 segments were imaged and analyzed by both contrast-enhanced 64-MDCT and IVUS. Sixteen segments were ruled out because of poor CT image quality. Compared with IVUS, 64-MDCT enabled correct detection in 86 of 89 (96.6%) segments containing noncalcified plaques, 25 of 27 (92.6%) segments containing calcified plaques, and 118 of 131 (90.1%) segments without atherosclerotic plaques. Sensitivity, specificity, positive predictive value, and negative predictive value for the detection of plaques by 64-MDCT were 97.4%, 90.1%, 89.7%, and 97.5%, respectively. Plaque analysis software using predetermined Hounsfield unit ranges for different components of plaque was able to distinguish between fibrous, fibrous-soft, and calcified plaques to a significant degree, but was less able to distinguish between soft and fibrous, and between soft and fibrous-soft plaque. Cohen's kappa coefficient for the sole detection of atherosclerotic segments by observers was 0.91. The correlation coefficients to determine vascular CSA, luminal CSA, and plaque burden were r = 0.85, 0.82, and 0.77, respectively (p < 0.01).
CONCLUSION. Compared with IVUS, contrast-enhanced 64-MDCT has a good ability to identify and quantify coronary atherosclerotic plaques. However, the reliable differentiation of the composition of noncalcified plaques is still limited.
Keywords: atherosclerotic plaque • coronary artery • intravascular ultrasound • MDCT
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64-MDCT Technique
Patients with heart rates greater than 70 beats per minute received
25–50 mg of metoprolol orally 60 minutes before MDCT (Aquilion 64,
Toshiba). MDCT data were acquired using an X-ray beam collimation width of 32
mm (0.5-mm slice thickness x 64 rows) with the spatial resolution in
x-, y-, and z-axes of 0.35 mm, a gantry rotation of 400
milliseconds, a pitch of 11.2–13.2, an electric current of 350–450
mAs, and a tube voltage of 120–135 kV (depending on patient size).
Contrast medium (70–85 mL, 370 mg I/mL, depending on patient size) was injected IV at 4 mL/s followed by a 40-mL saline flush at the same injection rate. The CT value of the area of interest in the ascending aorta was monitored from the start of the injection. As soon as the CT value in the ascending aorta reached 130–150 H, scanning was manually initiated, and imaging of the entire volume of the heart was acquired during one breath-hold with simultaneous recording of the ECG tracing.
Axial images (slice thickness, 0.5 mm; increment, 0.3 mm) were reconstructed using a multisector reconstruction algorithm. Using retrospective ECG gating, we routinely performed reconstructions at 75% of the R-R interval. If motion artifacts existed at these reconstructions, another, more optimal ECG phase was chosen to provide better image quality.
64-MDCT Image Analysis
The baseline axial images were postprocessed and analyzed by plaque
analysis software (Sure Plaque, Toshiba) at the workstation (HP XW8200,
Hewlett-Packard). The software detected both plaques and vessel walls on CT
images. Different CT density ranges hypothesized to represent different
components of plaque were displayed with various colors. Specifically, the
lipid composition (range, –100 to 29 H) was represented by red; fibrous
composition (range, 30–189 H) was represented by blue; calcification
(range, 350–1,000 H) was represented by yellow; lumen (range,
190–349 H) was represented by green; and vessel wall (range,
30–189 H; same range as for fibrous composition) was represented by
luteous. The Hounsfield unit ranges for plaque were preset by software and
could be manually altered by the operator. The ranges should be adjusted
slightly to avoid the influence of lumen density and obtain more accurate
quantitative measurements. The mean density in the contrast-enhanced lumen of
the proximal coronary artery (American Heart Association [AHA] segments 1, 5,
6, and 11) and the Hounsfield unit range of the vessel wall, adjusted to equal
the IVUS image in size, were recorded. The results of this analysis revealed
that when the average intensity in the lumen of the proximal artery is >
380 H, the optimal setting to detect plaque and the outer vessel boundaries is
obtained at the CT vessel wall range of 30–189 H; however, when the
average intensity of the proximal lumen is < 380 H, a CT vessel wall range
of 20–179 H is optimal.
For comparisons with IVUS, the target coronary arteries were divided into 10-mm segments from the ostium or onset [2, 3]. Segments with artifacts or blur images were excluded. Plaque qualitative analysis included determinations of the presence and classification of plaque in each coronary segment. Atherosclerotic plaques were considered present when the vessel wall thickness exceeded 0.5 mm. Each plaque was classified according to the color displayed by the software. Plaques displayed as red or green were classified as noncalcified plaque. Plaques with yellow present were defined as calcified plaque without considering the calcified size. Luminal cross-sectional area (CSA) (mm2), vascular CSA—that is, external elastic membrane CSA in IVUS—and plaque burden (%) (defined as external elastic membrane CSA minus the luminal CSA and then divided by the external elastic membrane CSA again) were measured in each 10-mm interval cross section. Two investigators blinded to the IVUS results who were not involved in the later comparative analysis, performed these analyses independently [5].
64-MDCT Density Measurements
Five well-distributed regions of interest (ROIs), each with a 1
mm2 area, were selected in each plaque. The CT density of each ROI
area was measured and recorded. The mean density was calculated by averaging
the density measurements. Density measurements for calcification were
performed only in hyperdense parts of the calcified plaques. To obtain
accurate and complete density of noncalcified plaques, entire plaques were
measured instead of hypodense tissue areas only
[2]. Densities of different
types (soft, fibrous, and fibrous-soft plaques) of noncalcified plaques
corresponding to IVUS detection were retrospectively calculated.
Intravascular Ultrasound
IVUS was performed as part of the invasive diagnostic procedure. After
coronary angiography, the patients were given intracoronary administration of
0.2 mg of nitroglycerin before introduction of the IVUS catheter. A Volcano
Eagle Eye IVUS catheter (20-MHz, electronic transducer, Volcano) was used. The
ultrasound catheter was positioned sufficiently distal (30 mm distal) to the
targeted site, and motorized pullback at a speed of 0.5 mm/s was used.
The IVUS data were stored digitally and assessed offline by the software configuration of the IVUS system. As with MDCT, 10-mm segments were analyzed. The external elastic membrane CSA, equal to the vascular CSA in CT analysis, luminal CSA, and plaque burden were calculated by software after the borders of vessel intima and adventitia were depicted manually in each detectable cross section. These quantitative measurements were performed in accordance with the IVUS interpretation recommendations of the American College of Cardiology (ACC) [1]. According to the ACC recommendations, atherosclerotic plaques were defined as lesions located between the media and the intima with a thickness of at least 0.5 mm. Calcified plaques were defined as plaque tissue containing any tissue with an echogenicity as bright as, or brighter than, the adventitia causing acoustic shadows. Noncalcified plaques were defined as plaque tissue without acoustic shadows, including soft (hypoechoic) plaques, defined as plaque tissue revealing an echogenicity lower than the adventitia, and fibrous (hyperechoic) plaques, having an echogenicity as bright as, or brighter than, the adventitia. Plaques containing more than one acoustical subtype were considered mixed plaques. Fibrous-soft plaques were defined as plaques in which hypoechoic and hyperechoic lesion occupied approximately 50% of the plaque area, respectively, Two investigators, blinded to the CT results, independently determined the presence, classification, and quantitative measurement of athero-sclerotic plaque in IVUS images.
Comparison of IVUS Versus 64-MDCT
In this study, both 64-MDCT and IVUS were performed in 40 coronary arteries
with moderate (50–75%) to significant (> 75%) coronary artery
stenoses on conventional angiography, including three right coronary arteries
(RCA), 14 left main arteries (LMA), 20 left anterior descending arteries
(LAD), and three left circumflex arteries (LCX). Coronary atherosclerotic
plaques often involve a large segment or the entire coronary vessel;
therefore, the target coronary trees were divided into 10-mm segments on the
basis of their distance to the ostium
[2,
6]. The complete distance of
the target artery from the distal reference point to the coronary ostium was
measured using the longitudinally reconstructed IVUS data set and multiplanar
reconstructions of the CT data set. Furthermore, we selected fiduciary points,
such as side branches, characteristic calcifications, or stents, to ensure
that the same corresponding coronary sections were compared. Each segment was
morphologically classified according to IVUS and CT criteria. Noncalcified
plaques defined by CT images included the soft, fibrous, and fibrous-soft
plaques in IVUS; and calcified plaques defined by CT images were equal to the
ones in IVUS, including fibrous calcified plaques. The comparison between
64-MDCT and IVUS was on a segmental basis for qualitative analysis and on a
site-by-site basis for quantitative analysis. A measurement discrepancy of 1
mm per vessel section was tolerated.
Statistical Analysis
Sensitivity and specificity of MDCT for detection of any plaque were
calculated on a segment-per-segment basis. Cohen's kappa statistic was
calculated to determine interobserver agreement in detecting plaque. The
interobserver variability for 64-MDCT quantitative measurements was calculated
[3]. To compare the mean
density values of different plaque types, the nonparametric Kruskal-Wallis
test was used. For comparison of the external elastic membrane CSA, luminal
CSA, and plaque burden obtained by 64-MDCT and IVUS, the Spearman's rank
correlation coefficient was determined. The paired Student's t test
was used to test for potential differences between those parameters obtained
by both methods. A p value < 0.05 was considered statistically
significant. All calculations were performed using the SPSS13 software package
(SPSS).
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The Spearman's rank correlation coefficients of vascular CSA (external elastic membrane CSA), luminal CSA, and plaque burden determined by 64-MDCT and IVUS were r = 0.85, 0.82, and 0.77, respectively (p < 0.01; Fig. 4A, 4B, 4C). The paired Student's t test showed that luminal CSA was underestimated by 64-MDCT (5.81 ± 3.32 mm2 vs 6.32 ± 3.04 mm2; p < 0.01). External elastic membrane CSA and plaque burden were overestimated by 64-MDCT (17.02 ± 5.79 mm2 vs 16.07 ±6.30 mm2 and 61.02% ± 16.02% vs 56.25% ± 16.07%, respectively; p < 0.05). The interobserver variability for plaque quantitative measurements by 64-MDCT was 12%. Cohen's kappa coefficient for the sole detection of atherosclerotic segments was 0.91, indicating good agreement.
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Better results obtained in our study depended not only on high spatial and temporal resolution of 64-MDCT but also on the application of plaque analysis software. This semiautomatic tool can accurately detect plaque compared with IVUS and can also distinguish between calcified and noncalcified plaque. The morphology of coronary plaques could be visualized and quantified. Software assessment allowed detailed investigation of plaques by color-coding on preset Hounsfield unit ranges. Hence, contrast-enhanced lumen, vessel wall, and even plaque composition (soft, fibrous, or calcified) could be depicted in different colors according to their corresponding CT Hounsfield unit ranges. Furthermore, this software was able to describe plaque morphology more clearly and to perform quantitative analysis of plaque. Note that the lumen and vessel wall of coronary arteries had no obvious border on CT images because of limited spatial resolution and because of smaller vascular sections compared with the carotid and aortic arteries. Thus, software could provide more rapid and accurate detection of plaques by CT range settings than by a manual method of depicting the inner and outer borders of the vessel wall; the software was also less observer-dependent than manual adjustments of window and level [3, 8].
Noncalcified plaque may be more unstable and prone to rupture than calcified plaque. Recent studies have shown that CT can identify noncalcified plaques in the coronary arteries in vivo [9–11]; moreover, CT features of noncalcified and calcified plaques correlate well with histopathologic stages of atherosclerosis [12]. Research by Ehara et al. [13] suggested that spotty distribution of calcium is of greater predictive value for acute coronary syndromes than the overall quantity. Twenty-five of 27 (92.6%) calcified plaques were found in our study, which missed two plaques containing small calcifications. Such high sensitivity for the detection of calcium with 64-MDCT is helpful for risk stratification in patients with coronary atherosclerotic disease.
CT density of plaque correlates with echogenicity of IVUS, and CT attenuation reflects major plaque composition. 64-MDCT can assess the thickness of the athero-sclerotic wall directly and can identify a large lipid core, superficial calcified nodules, and outward remodeling as morphology characteristics of vulnerable plaque [13–16]. Granted, improving CT detection of plaque with automated software is progress toward understanding plaque composition and its natural history. However, it is many steps away from identifying the high-risk "vulnerable" plaque.
Lipid-rich, fibrous, and calcified plaques displayed different CT densities and can be reliably differentiated. In our results, the mean CT density values for soft, fibrous, and calcified plaques were 72 ± 36 H, 90 ± 27 H, and 772 ± 251 H, respectively. Similar investigations showed these values to be 14 ± 26 H, 91 ± 21 H, and 419 ± 194 H, respectively [8], and 49 ± 22 H, 91 ± 22 H, and 391 ± 156 H [2]. However, it remains difficult to determine the definite composition of individual noncalcified plaques, even if there is a significant difference in CT Hounsfield units among components. For example, hypodense areas in plaque could represent various tissue types, including lipid pool, less dense fibrous tissue, neovascularized areas, and thrombus. Moreover, in our study, CT found some noncalcified plaques with homogeneous echogenicity in IVUS that showed inhomogeneous density on CT, detected lipid pools (hypodense spots) in three of five (60%) segments, and could not discriminate the fibrous cap. Therefore, the accuracy for identifying noncalcified plaque components such as lipid-rich (soft) or fibrotic components remains low [17, 18].
The mean CT density values measured in our study were higher than those of other studies [2, 8]. The reason may be that the concentration of contrast material we used (370 mg I/mL) was higher than that used in other studies (300 or 350 mg I/mL). With 370 mg I/mL, we obtained a mean contrast enhancement in the coronary lumen of normal proximal segments of 398 ± 74 H, higher than the 343 ± 55 H measured by Achenbach et al. [7] using 350 mg I/mL contrast medium. It was assumed that plaque density is partly influenced by contrast enhancement in the coronary lumen; the CT densities of smaller and soft plaques were often elevated by greater enhancement in the lumen.
A significant trend was seen to underestimate luminal CSA and overestimate plaque burden. However, this study was designed to determine the accuracy of 64-MDCT without excluding significant stenosis. Significant stenosis causes decreased contrast enhancement of the lumen in corresponding segments. If we analyze proximal coronary arteries without significant stenosis, it is possible that better correlation between IVUS and CT would be obtained.
Sure Plaque software has the following technical limitations. First, the maximum number of images on which Sure Plaque software can be performed is only 512. Second, the z-direction size is less than the x, y-direction size. There are no standard recommendations for absolute density results of Sure Plaque tools. It is difficult to further differentiate or classify the noncalcified plaque because of the overlap of CT values of different composition in noncalcified plaque. Several limitations are also inherent in contrast-enhanced 64-MDCT itself, including restrictions of its spatial and temporal resolution [2, 19, 20]. Partial volume effects caused by large coronary calcifications and lumen contrast enhancement are frequently considered to be false-positive and false-negative results. Furthermore, contrast enhancement of the lumen may overlap, and thus conceal, superficial and smaller areas of calcium with 64-MDCT.
In summary, 64-MDCT is a useful noninvasive method and has good ability to detect, differentiate, and quantify coronary athero-sclerotic plaques. It may be used to improve risk stratification in patients with suspected or known coronary atherosclerotic disease and to monitor progression or regression of coronary atherosclerosis. However, the reliable differentiation of the composition of individual noncalcified plaques is still limited.
Acknowledgments
We are indebted to the medical and technical staff members of the CT and
ultrasound departments for their invaluable contribution, and in particular to
Yike Zhao, Hong Jiang, Haixia Yang, and Yanhong Wang for their expert
technical assistance.
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