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Arterial Wall Imaging: Evaluation with 16-Section Multidetector CT in Blood Vessel Phantoms and ex Vivo Coronary Arteries¹

¹ From the Department of Radiology (M.F., R. C. Chan, J.B.L., U.H., S. Abbara, R. C. Cury, T.J.B.), Wellman Laboratories of Photomedicine (R. C. Chan, B.E.B., G.J.T.), and Department of Pathology (S.L.H., G.J.T.), Massachusetts General Hospital and Harvard Medical School, 165 Cambridge St, Suite 400, Boston, MA 02114; and Department of Medicine II, University of Erlangen, Erlangen, Germany (S. Achenbach). Received July 18, 2005; revision requested September 28; revision received October 24; accepted December 2; final version accepted December 15. Supported in part by National Institutes of Health Radiological Science Training grant 5-T32 Ca 09362 E20, the Center for the Integration of Medicine and Innovative Technology, and the New York Cardiac Center. S. Achenbach supported by Deutsche Forschungsgemeinschaft. Address correspondence to M.F. (e-mail: maros_ferencik{at}hms.harvard.edu), R. C. Chan (e-mail: rchan{at}alum.mit.edu).

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION ADVANCES IN KNOWLEDGE References

 
Purpose: To evaluate the diagnostic performance of 16-section multidetector computed tomography (CT) for assessment of plaques in phantoms and ex vivo coronary arteries, with intravascular ultrasonography (US) and optical coherence tomography (OCT) as reference standards.

Materials and Methods: Research protocol was HIPAA compliant and approved by institutional review board, without informed consent required. Blood vessel and lesion composition phantoms and ex vivo coronary arteries were imaged with 16-section CT. Wall areas of phantoms and ex vivo coronary arteries were measured with multidetector CT and intravascular US. Sensitivity and specificity for lipid detection were determined in lesion composition phantoms. CT numbers of blood vessel wall were determined in ex vivo coronary arteries and compared with lesion classification results from OCT. Agreement in dimensional measurements was compared (paired t tests). CT numbers within blood vessel wall of CT cross sections classified as lipid rich, fibrous, and calcified at OCT were compared (Kruskal-Wallis tests).

Results: Mean blood vessel wall areas measured with CT and US in phantoms were 9.2 mm² ± 1.8 (standard deviation) and 10.4 mm² ± 3.4 (bias, –1.3 mm² ± 3.1; P < .05), respectively. Mean blood vessel wall areas measured in ex vivo coronary arteries with CT and US were 10.9 mm² ± 4.1 and 9.1 mm² ± 3.1 (bias, 1.8 mm² ± 3.0; P < .001), respectively. Sensitivity and specificity of 93% and 92%, respectively, for identification of lipid-rich lesions were observed in lesion composition phantoms. Mean CT numbers in blood vessel wall of ex vivo coronary arteries identified at OCT as predominantly lipid rich, fibrous, and calcified were 29 HU ± 43, 101 HU ± 21, and 135 HU ± 199, respectively (P < .001).

Conclusion: Determination of composition of individual plaques from attenuation values can be more challenging because of overlapping values for different tissue types.

© RSNA, 2006

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION ADVANCES IN KNOWLEDGE References

 
Multidetector computed tomography (CT) has evolved as a potential tool for noninvasive assessment of coronary arterial atherosclerotic plaque. In initial reports, investigators showed the capability of four-section multidetector CT systems to depict noncalcified coronary plaques (1) and explored the feasibility of further differentiation of plaques into lipid-rich and fibrous types (2–6).

Improvements in the imaging of coronary arterial plaque were achieved with the introduction of 16-section multidetector CT. Submillimeter collimation and faster gantry rotation allowed enhanced image quality (7) and reliable detection of hemodynamically significant coronary stenoses (8–13). The sensitivity and specificity of 16-section multidetector CT compared with intravascular ultrasonography (US) for detection of coronary plaque were 75%–82% and 88%–92%, respectively (14,15). Initial results with multidetector CT have indicated that there have been improvements in quantification of coronary plaque dimensions in patients (16–18). Differentiation of coronary atherosclerotic lesions into calcified and noncalcified components is possible (14,15). Researchers in recent studies (15,19,20) have shown the potential application of multidetector CT for differentiation of lipid-rich and fibrous plaque on the basis of attenuation measurements. Thus, the purpose of our study was to evaluate the diagnostic performance of 16-section multidetector CT for assessment of plaque dimension and composition in phantoms and ex vivo coronary arteries, with intravascular US and optical coherence tomography as the reference standards.

	MATERIALS AND METHODS

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Blood Vessel Phantoms
Phantoms (n = 9) for evaluation of blood vessel dimension were constructed from polyvinyl alcohol hydrogel (Lentikat; geniaLab BioTechnologie, Braunschweig, Germany), with cylindric molds ranging from 1.7 to 3.1 mm in inner diameter and from 3.0 to 4.8 mm in outer diameter (Fig 1, Table 1). To mimic diseased blood vessels with wall thicknesses that varied between 0.7 and 3.0 mm, "plaques" (n = 34) consisting of polyvinyl alcohol fragments that ranged in thickness from 0.6 to 1.5 mm were attached to the outer surface of the blood vessel phantoms. The CT attenuation value of the hydrogel was 60–95 HU, which was within the range typical of fibrous tissue (4,6,15,19,20). The blood vessel phantoms were first imaged with intravascular US and then with multidetector CT. Prior to multidetector CT, a polysaccharide gel (Kelcogel; CP Kelco, Wilmington, Del) mixed with iopromide (Ultravist; Schering, Berlin, Germany), 300 mg of iodine per milliliter, at a proportion of 50:1 was injected into the lumen to achieve enhancement (approximately 250 HU) typical of in vivo multidetector CT (14).

View larger version (71K): [in this window] [in a new window] [Download PPT slide]   Figure 1: Gross cross sections of a blood vessel phantom made from polyvinyl alcohol hydrogel, with lumen (*) indicated. "Plaque" (arrow) consisted of polyvinyl alcohol gel fragments.

The CT attenuation value of fibrous tissue was simulated with a solution consisting of 57 mL of the same contrast agent with the same amount of iodine in 10 mL of water. The mean CT attenuation value of the solution that represented fibrous tissue was 99 HU. This solution was emulsified with an aqueous lipid suspension (Intralipid; Kabivitrum, Alameda, Calif) in varying proportions to produce different lesion compositions. Five lesion compositions were prepared: These lesion compositions had lipid-fibrous volume ratios of 10:90, 20:80, 30:70, 40:60, 100:0, with mean CT attenuation values of 69, 47, 23, –2, and –141 HU, respectively. Comparison of these values with previously reported CT attenuation values in lipid-rich coronary arterial plaques (4,6,15,19,20) indicated that the CT attenuation values of our emulsions were within the range of attenuation values associated with lipid-containing tissue.

Ex Vivo Coronary Arteries
Eighteen human coronary arteries (six left anterior descending arteries, six left circumflex arteries, and six right coronary arteries) were obtained at autopsy from six subjects (four men, two women; mean age, 77 years ± 1 [standard deviation]). The arteries and perivascular tissue were excised, rinsed, and flushed to remove superficial thrombus. Coronary arteries that contained atherosclerotic plaque without extensive calcification (34% of heavily calcified segments were excluded) were cut into segments that ranged from 5 to 10 mm in length to facilitate registration with intravascular US and optical coherence tomography. The tissue samples were then immobilized within the polysaccharide gel and scanned with intravascular US and optical coherence tomography. Prior to multidetector CT, a solution of polysaccharide gel and contrast agent was injected into the segments to obtain a CT attenuation of approximately 250 HU in the lumen. Experiments were completed within 48 hours of harvesting.

The research protocol that involved human coronary arteries was approved by our institutional review board. Informed consent was not required from next of kin. The protocol complied with Health Insurance Portability and Accountability Act regulations.

Multidetector CT
All phantoms and ex vivo coronary arteries were placed into an anthropomorphic phantom (Cardio CT; Quality Assurance in Radiology and Medicine, Moehrendorf, Germany) that simulated the thorax in a human for imaging with a multidetector CT scanner (Sensation 16; Siemens Medical Solutions, Forcheim, Germany) (21). One investigator (M.F., with 3 years of experience in cardiac multidetector CT) obtained the scans. Phantoms and ex vivo coronary arteries were oriented parallel to the axis of the gantry rotation. A cardiac spiral imaging protocol was used (120 kV, 500 mAs, 16 detector rows and 0.75-mm section thickness, 0.42-second rotation time, 2.8 mm/sec table feed), together with a simulated electrocardiographic signal set to a heart rate of 60 beats per minute for retrospectively gated reconstruction. Transverse images were reconstructed with 0.75-mm section thickness, at 0.3-mm increments, with a 12-cm field of view (chosen to achieve the best available in-plane resolution of 7 line pairs per centimeter), a medium-smooth reconstruction filter (B35f), and a 512 x 512-pixel matrix.

Intravascular US
One investigator (R. C. Chan, with 10 years of experience in vascular US) performed intravascular US (Galaxy; Boston Scientific, Boston, Mass) in blood vessel phantoms and ex vivo arteries by using a 40-MHz probe (Atlantis; Boston Scientific) and a motorized pullback (0.5 mm/sec). Specimens were fixed to an examination tray. Images were digitized at 30 frames per second. Intravascular US, compared with histologic analysis, has been shown to be highly accurate for detection and quantification of coronary atherosclerotic plaque ex vivo (22,23).

Optical Coherence Tomography
One investigator (R. C. Chan, with 3 years of experience in optical coherence tomography) performed optical coherence tomography in ex vivo coronary arteries with a motorized pullback (0.5 mm/sec) by using a custom-built imaging system (24–26). Specimens were fixed to an examination tray. Images were digitally acquired and stored for analysis. Diagnostic evaluation was not performed in 30 of 194 cross sections because the cross sections were larger than the available field of view or because the optical coherence tomographic source power was unacceptable for diagnostic imaging during the particular imaging session.

Optical coherence tomography is a high-spatial-resolution optical imaging technique that provides cross-sectional images of coronary arteries (24–26) with an in-plane spatial resolution of 10 x 25 µm. This technology previously has been validated and was demonstrated to be highly sensitive and specific for distinguishing lipid-rich, fibrous, and calcified tissue (25,26). For our studies, optical coherence tomographic pullback imaging provided continuous interrogation of arterial composition in a manner that is impossible with histologic analysis. To avoid the difficulties of histologic section registration and artifacts typically associated with histologic processing, optical coherence tomography was deemed to be an acceptable standard of reference for our purposes.

Imaging of Gross Sections of Blood Vessel Phantom
After 16-section multidetector CT, blood vessel phantoms were sectioned transversely at regular intervals (2 mm) and photographed for use as a histologic equivalent reference (Fig 1). A ruler photographed with each cross section was used to calibrate spatial dimensions.

Analysis of Blood Vessel Phantoms
Analysis of blood vessel phantoms was performed with software (Matlab; MathWorks, Natick, Mass) for registered images from multidetector CT, intravascular US, and digitized gross section analysis (Fig 2). An independent observer (M.F., with 3 years of experience in cardiac multidetector CT) without prior knowledge about phantom characteristics manually segmented the multidetector CT images. Images were displayed with a fixed window setting (500-HU window width, 200-HU window level). A separate reader (R. C. Chan) who was blinded to the multidetector CT results manually segmented intravascular US images and digitized gross section data. The detected blood vessel boundaries at the inner and outer walls were then used to compute the luminal area, total cross-sectional area, and wall area (defined as the area between the inner and outer blood vessel boundaries) by using planimetric measurement.

View larger version (38K): [in this window] [in a new window] [Download PPT slide]   Figure 2a: (a) Cross sections of the blood vessel morphologic phantom imaged with multidetector CT (MDCT) and intravascular US (IVUS) and corresponding image from gross section analysis. The lumen of the vessel phantoms is marked (*), and intravascular US catheter is in the lumen (open arrow), also in b. Solid arrow points to the fibrous lesion mounted on the wall of the blood vessel morphologic phantom from outside. (b) Cross section of ex vivo coronary artery imaged with multidetector CT, intravascular US, and optical coherence tomography (OCT). An atherosclerotic plaque (arrowhead), characterized as lipid rich with optical coherence tomography, was noted at all three modalities.

View larger version (53K): [in this window] [in a new window] [Download PPT slide]   Figure 2b: (a) Cross sections of the blood vessel morphologic phantom imaged with multidetector CT (MDCT) and intravascular US (IVUS) and corresponding image from gross section analysis. The lumen of the vessel phantoms is marked (*), and intravascular US catheter is in the lumen (open arrow), also in b. Solid arrow points to the fibrous lesion mounted on the wall of the blood vessel morphologic phantom from outside. (b) Cross section of ex vivo coronary artery imaged with multidetector CT, intravascular US, and optical coherence tomography (OCT). An atherosclerotic plaque (arrowhead), characterized as lipid rich with optical coherence tomography, was noted at all three modalities.

View larger version (33K): [in this window] [in a new window] [Download PPT slide]   Figure 3: A single montage of all 270 20 x 20-pixel images of lesion composition phantom. Lipid core concentration increases from left to right and diameter decreases from top to bottom. Five images for each lipid core size and composition were evaluated.

Blood vessel dimensions were measured with software by using registered multidetector CT and intravascular US cross sections (Fig 2). For the evaluation, images were presented to readers in random order. An independent reader (M.F.) manually segmented the multidetector CT images. Each image was displayed with a fixed window setting (500-HU window width, 200-HU window level). Similarly, a separate reader (S. Achenbach, with 7 years of experience with intravascular US) who was blinded to the multidetector CT results manually segmented the intravascular US data. The detected boundaries were used to compute luminal area, total cross-sectional vessel area, and wall area by using planimetric measurement.

For analysis of ex vivo coronary arterial composition, paired-vessel cross sections from multidetector CT and optical coherence tomography were used (Fig 2). CT attenuation values within the vessel wall were automatically extracted from segmented multidetector CT data. For analysis of optical coherence tomographic data, an observer (G.J.T., with 10 years of experience in optical coherence tomography) who was blinded to multidetector CT results classified cross sections as those with lipid present (characterized by signal-poor regions with diffuse borders), those that were fibrous (characterized by homogeneous signal-rich regions), or those that were calcified (characterized by well-delineated signal-poor regions with sharp borders) (25,26).

Statistical Analysis
Results are expressed as the mean ± standard deviation unless specified otherwise. Agreement of dimensional measurements between modalities (multidetector CT vs intravascular US, multidetector CT vs gross section analysis) was compared with paired t tests, and measurement bias was calculated as the mean paired difference. For the analysis of lesion composition phantoms, sensitivity for detection, calculated as [true-positive findings/(true-positive findings + false-negative findings)], and specificity, calculated as [true-negative findings/(true-negative findings + false-positive findings)], were derived as a function of size and composition of lipid cores, compared with the ground truth.

For the analysis of ex vivo coronary arterial composition, CT attenuation values within the vessel wall of multidetector CT cross sections classified as lipid rich, fibrous, and calcified with optical coherence tomography were compared by using nonparametric Kruskal-Wallis tests. Results from analysis of ex vivo arterial composition were also displayed as histograms of attenuation measured within the walls of lipid-rich, fibrous, and calcified cross sections. Statistical analysis was performed by using software (Intercooled Stata 6.0; Stata, College Station, Tex). A P value of <.05 was considered to indicate a significant difference.

	RESULTS

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Blood Vessel Phantoms
Dimensional measurements were performed on 43 registered images (Table 2). Comparison of multidetector CT and intravascular US measurements of blood vessel wall area showed a mean bias of –1.3 mm² ± 3.1 with multidetector CT relative to intravascular US (P < .05). Multidetector CT measurements of blood vessel wall area compared with measurements at gross section analysis showed a mean bias of 0.3 mm² ± 3.8 (P = .59).

Lesion Composition Phantoms
The specificity of lesion assessment was 96% (43 of 45); however, the sensitivity for detection for any lipid cores between 0.4 and 4.0 mm in diameter was only 44% (100 of 225). The sensitivity for detection increased with increasing lesion diameter (Fig 4a). When we considered only lesions between 1.0 and 4.0 mm in diameter, the sensitivity increased to 63% (94 of 150). For lesions between 1.5 and 4.0 mm in diameter, the sensitivity for detection was even higher, at 71% (89 of 125). The specificity remained high for lipid lesions with larger diameters (Fig 4a).

View larger version (35K): [in this window] [in a new window] [Download PPT slide]   Figure 4a: (a) Graph shows sensitivity (white bars) and specificity (gray bars) for detection of lipid cores with increasing diameter and all lipid concentrations in lesion composition phantom. (b) Graph shows sensitivity for detection of lipid cores with 1.5-mm or larger diameter as a function of increasing lipid concentration.

View larger version (32K): [in this window] [in a new window] [Download PPT slide]   Figure 4b: (a) Graph shows sensitivity (white bars) and specificity (gray bars) for detection of lipid cores with increasing diameter and all lipid concentrations in lesion composition phantom. (b) Graph shows sensitivity for detection of lipid cores with 1.5-mm or larger diameter as a function of increasing lipid concentration.

The measured CT attenuation in detected lesions decreased with increasing lipid concentration. Lipid concentration, however, was not the only determinant of the measured attenuation value. The measured CT attenuation value for each lipid concentration also increased with decreasing lipid core diameter (Fig 5).

View larger version (34K): [in this window] [in a new window] [Download PPT slide]   Figure 5: Three-dimensional graph displays the dependence of the measured attenuation values on both diameter of lipid cores and their composition in lesion phantom.

View larger version (12K): [in this window] [in a new window] [Download PPT slide]   Figure 6: Correlation plot of wall area measurements in ex vivo coronary arteries from multidetector CT (MDCT) and intravascular US (IVUS).

View larger version (5K): [in this window] [in a new window] [Download PPT slide]   Figure 7a: Histograms of CT attenuation measurements in all pixels within the vessel wall of vessel cross sections from multidetector CT classified with optical coherence tomography as (a) lipid rich, (b) fibrous, and (c) calcified. "Frequency" on the y-axis reflects the fraction of pixels within the vessel wall with a particular CT attenuation value.

View larger version (5K): [in this window] [in a new window] [Download PPT slide]   Figure 7b: Histograms of CT attenuation measurements in all pixels within the vessel wall of vessel cross sections from multidetector CT classified with optical coherence tomography as (a) lipid rich, (b) fibrous, and (c) calcified. "Frequency" on the y-axis reflects the fraction of pixels within the vessel wall with a particular CT attenuation value.

View larger version (5K): [in this window] [in a new window] [Download PPT slide]   Figure 7c: Histograms of CT attenuation measurements in all pixels within the vessel wall of vessel cross sections from multidetector CT classified with optical coherence tomography as (a) lipid rich, (b) fibrous, and (c) calcified. "Frequency" on the y-axis reflects the fraction of pixels within the vessel wall with a particular CT attenuation value.

	DISCUSSION

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Coronary Arterial Plaque Dimensions
We analyzed the performance of 16-section multidetector CT for the measurement of blood vessel dimensions with ideal imaging conditions in phantoms and ex vivo coronary arteries. In phantoms, the measured wall areas were underestimated relative to measurements with intrasvascular US. Luminal area and total cross-sectional area measurements were not significantly different between the two modalities. With measurements on images from multidetector CT compared with those on images from gross section analysis, an overestimation of luminal and total cross-sectional area was observed. The smaller areas observed on images from gross section analysis may be explained by slight shrinkage of the polyvinyl alcohol gel after the sectioning of the phantoms.

We observed overestimation of area measurements with multidetector CT, compared with intravascular US, in ex vivo coronary arteries. Similar differences were observed in one previous study in which wall and luminal area measurements obtained at multidetector CT and intravascular US were compared in patients (18). The key factors that account for differences between measurements obtained at multidetector CT and intravascular US with optimal conditions are spatial resolution at multidetector CT and intravascular US and the partial volume effects at multidetector CT.

Coronary Arterial Plaque Composition
Our data from composition phantoms indicate that 16-section multidetector CT can depict lipid-rich lesions (1.5 mm in diameter, 30% lipid) within fibrous tissue with a sensitivity of 93% (70 of 75) and a specificity of 92% (23 of 25). In subjects with acute coronary arterial events, typical lipid core dimensions are in the range of 1–5 mm², and more than 80% of plaques have core areas larger than 1.0 mm² (27,28). Thus, 16-section multidetector CT has the potential for detection of lesions that cause acute events. In ex vivo coronary arteries, we observed significant differences in the distribution of attenuation for lipid-rich, fibrous, and calcified plaques. This finding highlights the potential of multidetector CT for use in the characterization of plaque composition.

Voxels within the blood vessel wall, however, encompassed a wide range of attenuation values for each cross section of a vessel and plaque type. This observation reflects the complexity of atherosclerotic plaques in which lipid-rich, fibrous, and calcified areas coexist and often are intermixed (27,29,30). In addition to the intrinsic complexity of biologic specimens, multidetector CT, even with thin-section 16-section scanners, is associated with partial volume effects and interpolation artifacts (31). Thus, the measured attenuation in small structures (eg, lipid cores) can be strongly influenced by attenuation in the surrounding tissue. This was confirmed in our lesion phantom experiments (Fig 5), and the results of those experiments indicate that CT attenuation within lipid cores varies not only with the percentage of lipid present but also with the size of the cores. Finally, beam-hardening artifacts may cause low attenuation measurements in pixels that surround calcified nodules (31). Low CT attenuation values were observed in cross sections of calcified tissue, and those pixels could represent either lipid-rich tissue in close proximity to calcium, as is often observed histologically (27,29,30,32), or beam-hardening artifacts.

Other investigators have used 16-section multidetector CT for differentiation of fibrous and lipid-rich plaques in ex vivo popliteal arteries (19), in a rabbit experimental model of aortic atherosclerosis (20), and in patients (15). With data similar to our findings, these investigators observed a significant difference between CT attenuation values measured from lipid-rich plaques as opposed to attenuation values measured from fibrous plaques. They also observed a substantial overlap of attenuation values. Therefore, determination of the composition of individual plaques and discrimination of intraplaque components (eg, lipid core, fibrous cap) remain extremely challenging due to the limited spatial resolution and soft-tissue contrast of current multidetector CT technology.

We found that the specific methods used for CT attenuation measurement are very important. Slight differences in the positioning of regions of interest may substantially affect the classification of plaque composition that is based on measured attenuation values. We suggest that measurements should be performed within the entire region recognized as plaque. Because of the limited spatial resolution of multidetector CT, the normal blood vessel wall (thickness, <300 µm) cannot be detected. Thus, any structure depicted as coronary plaque should be segmented and measured. Composition assessment that is based on selection of small regions of interest within a given plaque volume is sensitive to imaging noise and other artifacts. In addition, this selection method may introduce a bias toward structures that are different from the substantial tissue component of the plaque volume.

Limitations
Phantom models only roughly represent vascular atherosclerosis. For experiments in ex vivo coronary arterial samples, selection bias could have been introduced by the exclusion of heavily calcified arterial segments (34% of segments were excluded). These segments could not be evaluated on multidetector CT images because of blooming artifacts introduced by partial volume effects of large calcifications (31). Heavily calcified segments also could not be evaluated with intravascular US because of acoustic shadowing, which obscures the location of the external elastic lamina. In addition, 30 of 194 cross sections had to be excluded because of insufficient optical coherence tomographic image quality. The effects of physiologic motion on dimension and composition assessment were not considered in these experiments. In this work, the vessel phantoms and ex vivo coronary arteries were imaged within a chest torso phantom to mimic clinical scanning. The exact conditions observed in vivo, however, are only crudely approximated with the torso phantom. In clinical studies, tissue composition, patient size, and other factors can affect image quality (eg, image noise) and would have an effect on the measurements of blood vessel dimensions and assessment of plaque composition. Finally, a single fixed window setting was used for the evaluation of multidetector CT images. A similar fixed–window setting approach has been successfully applied in prior work on coronary plaque assessment with multidetector CT (17,18,20).

Histologic analysis is the current reference standard for the evaluation of coronary arterial atherosclerotic plaque. We did not use histologic analysis as a reference standard in this study. Instead, multidetector CT was compared with intravascular US and optical coherence tomography. Researchers in previous studies (22,23) clearly demonstrated the feasibility of coronary arterial atherosclerotic plaque size measurements by using intravascular US. The assessment of plaque composition with optical coherence tomography was extensively validated with histologic analysis (24–26). Intravascular US and optical coherence tomographic pullback imaging provided continuous interrogation of arterial composition in a manner that is impossible with histologic analysis. In addition, this approach also provided better section registration.

Practical application: The dimensional measurements of plaque obtained with 16-section multidetector CT performed with controlled ex vivo conditions were observed to be very similar to those obtained from in vivo observations in our study. The establishment of reliability of quantitative dimensional measurements of plaque obtained with multidetector CT paves the way for further studies focused on multidetector CT–based plaque burden and remodeling assessment for prediction of coronary arterial events.

The results of our studies in phantoms indicate that only larger lipid cores can be detected with the current generation of multidetector CT scanners. Large lipid cores are, however, typically found in lesions associated with acute coronary arterial syndromes (27,28). Thus, our study results suggest that multidetector CT has the potential to be used in plaque screening for detection of lesions with large lipid cores. Determination of the composition of individual plaques on the basis of CT attenuation measurements can be confounded by the size of the plaque itself and the CT attenuation of surrounding structures.

Multidetector CT, compared with intravascular US, permits measurement of plaque dimensions with optimal multidetector CT conditions (eg, low image noise) and without motion in phantoms and ex vivo coronary arteries, and the mean CT attenuation values of lipid-rich, fibrous, and moderately calcified plaques in ex vivo coronary arteries are significantly different. Multidetector CT–based noninvasive quantification of plaque burden is, therefore, promising for clinical evaluation of coronary arterial disease in patients. The assessment of plaque composition is more challenging, however. Overlapping attenuation characteristics in lipid-rich and fibrous plaque categories make determination of plaque type for individual cases difficult.

	ADVANCES IN KNOWLEDGE

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION ADVANCES IN KNOWLEDGE References

 

• Multidetector CT, compared with intravascular US, permitted measurement of plaque dimensions in phantoms and ex vivo coronary arteries, with the mean measurement bias of –1.3 mm² ± 3.1 and 1.8 mm² ± 3.0, respectively.
  
• The mean CT attenuation values of lipid-rich, fibrous, and moderately calcified plaques in ex vivo coronary arteries are significantly different; however, determination of the composition of individual plaques on the basis of CT attenuation can be more challenging because of overlapping attenuation values for different tissue types.
  

	FOOTNOTES

 
² Current address: Philips Research, Clinical Sites Research Program (Massachusetts General Hospital), Briarcliff Manor, NY.

Authors stated no financial relationship to disclose.

Author contributions: Guarantors of integrity of entire study, M.F., R. C. Chan, T.J.B.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; literature research, M.F., R. C. Chan, S. Achenbach, J.B.L., T.J.B.; experimental studies, all authors; statistical analysis, M.F., R. C. Chan; and manuscript editing, all authorsM.F. and R. C. Chan contributed equally to this work.

	References

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION ADVANCES IN KNOWLEDGE References

 

1. Becker CR, Knez A, Ohnesorge B, Schoepf UJ, Reiser MF. Imaging of noncalcified coronary plaques using helical CT with retrospective ECG gating. AJR Am J Roentgenol 2000;175:423–424.[Free Full Text]
2. Schroeder S, Kopp AF, Baumbach A, et al. Noninvasive detection and evaluation of atherosclerotic coronary plaques with multislice computed tomography. J Am Coll Cardiol 2001;37:1430–1435.[Abstract/Free Full Text]
3. Schroeder S, Flohr T, Kopp AF, et al. Accuracy of density measurements within plaques located in artificial coronary arteries by x-ray multislice CT: results of a phantom study. J Comput Assist Tomogr 2001;25:900–906.[CrossRef][Medline]
4. Nikolaou K, Becker CR, Muders M, et al. Multidetector-row computed tomography and magnetic resonance imaging of atherosclerotic lesions in human ex vivo coronary arteries. Atherosclerosis 2004;174:243–252.[Medline]
5. Inoue F, Sato Y, Matsumoto N, Tani S, Uchiyama T. Evaluation of plaque texture by means of multislice computed tomography in patients with acute coronary syndrome and stable angina. Circ J 2004;68:840–844.[CrossRef][Medline]
6. Schroeder S, Kuettner A, Leitritz M, et al. Reliability of differentiating human coronary plaque morphology using contrast-enhanced multislice spiral computed tomography: a comparison with histology. J Comput Assist Tomogr 2004;28:449–454.[CrossRef][Medline]
7. Ferencik M, Moselewski F, Ropers D, et al. Quantitative parameters of image quality in multidetector spiral computed tomographic coronary imaging with submillimeter collimation. Am J Cardiol 2003;92:1257–1262.[CrossRef][Medline]
8. Ropers D, Baum U, Pohle K, et al. Detection of coronary artery stenoses with thin-slice multi-detector row spiral computed tomography and multiplanar reconstruction. Circulation 2003;107:664–666.[Abstract/Free Full Text]
9. Nieman K, Cademartiri F, Lemos PA, Raaijmakers R, Pattynama PM, de Feyter PJ. Reliable noninvasive coronary angiography with fast submillimeter multislice spiral computed tomography. Circulation 2002;106:2051–2054.[Abstract/Free Full Text]
10. Martuscelli E, Romagnoli A, D'Eliseo A, et al. Accuracy of thin-slice computed tomography in the detection of coronary stenoses. Eur Heart J 2004;25:1043–1048.[Abstract/Free Full Text]
11. Dewey M, Laule M, Krug L, et al. Multisegment and halfscan reconstruction of 16-slice computed tomography for detection of coronary artery stenoses. Invest Radiol 2004;39:223–229.[CrossRef][Medline]
12. Hoffmann U, Moselewski F, Cury RC, et al. Predictive value of 16-slice multidetector spiral computed tomography to detect significant obstructive coronary artery disease in patients at high risk for coronary artery disease: patient-versus segment-based analysis. Circulation 2004;110:2638–2643.[Abstract/Free Full Text]
13. Kuettner A, Beck T, Drosch T, et al. Diagnostic accuracy of noninvasive coronary imaging using 16-detector slice spiral computed tomography with 188 ms temporal resolution. J Am Coll Cardiol 2005;45:123–127.[Abstract/Free Full Text]
14. Achenbach S, Moselewski F, Ropers D, et al. Detection of calcified and noncalcified coronary atherosclerotic plaque by contrast-enhanced, submillimeter multidetector spiral computed tomography: a segment-based comparison to intravascular ultrasound. Circulation 2004;109:14–17.[Abstract/Free Full Text]
15. Leber AW, Knez A, Becker A, et al. Accuracy of multidetector spiral computed tomography in identifying and differentiating the composition of coronary atherosclerotic plaques: a comparative study with intracoronary ultrasound. J Am Coll Cardiol 2004;43:1241–1247.[Abstract/Free Full Text]
16. Schoenhagen P, Tuzcu EM, Stillman AE, et al. Non-invasive assessment of plaque morphology and remodeling in mildly stenotic coronary segments: comparison of 16-slice computed tomography and intravascular ultrasound. Coron Artery Dis 2003;14:459–462.[CrossRef][Medline]
17. Achenbach S, Ropers D, Hoffmann U, et al. Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography. J Am Coll Cardiol 2004;43:842–847.[Abstract/Free Full Text]
18. Moselewski F, Ropers D, Pohle K, et al. Measurement of cross-sectional coronary atherosclerotic plaque and vessel areas by 16-slice multi-detector CT: comparison to IVUS. Am J Cardiol 2004;94:1294–1297.[CrossRef][Medline]
19. Schroeder S, Kuettner A, Wojak T, et al. Non-invasive evaluation of atherosclerosis with contrast enhanced 16 slice spiral computed tomography: results of ex vivo investigations. Heart 2004;90:1471–1475.[Abstract/Free Full Text]
20. Viles-Gonzalez JF, Poon M, Sanz J, et al. In vivo 16-slice, multidetector-row computed tomography for the assessment of experimental atherosclerosis: Comparison with magnetic resonance imaging and histopathology. Circulation 2004;110:1467–1472.[Abstract/Free Full Text]
21. Quality assurance in radiology and medicine. QRM Web site. http://www.qrm.de/index2.html. Accessed October 18, 2005.
22. Gussenhoven EJ, Essed CE, Lancee CT, et al. Arterial wall characteristics determined by intravascular ultrasound imaging: an in vitro study. J Am Coll Cardiol 1989;14:947–952.[Abstract]
23. Nissen SE, Yock P. Intravascular ultrasound: novel pathophysiological insights and current clinical applications. Circulation 2001;103:604–616.[Abstract/Free Full Text]
24. Tearney GJ, Jang IK, Kang DH, et al. Porcine coronary imaging in vivo by optical coherence tomography. Acta Cardiol 2000;55:233–237.[CrossRef][Medline]
25. Jang IK, Bouma BE, Kang DH, et al. Visualization of coronary atherosclerotic plaques in patients using optical coherence tomography: comparison with intravascular ultrasound. J Am Coll Cardiol 2002;39:604–609.[Abstract/Free Full Text]
26. Yabushita H, Bouma BE, Houser SL, et al. Characterization of human atherosclerosis by optical coherence tomography. Circulation 2002;106:1640–1645.[Abstract/Free Full Text]
27. Virmani R, Burke AP, Kolodgie FD, Farb A. Vulnerable plaque: the pathology of unstable coronary lesions. J Interv Cardiol 2002;15:439–446.[Medline]
28. Ge J, Chirillo F, Schwedtmann J, et al. Screening of ruptured plaques in patients with coronary artery disease by intravascular ultrasound. Heart 1999;81:621–627.[Abstract/Free Full Text]
29. Stary HC, Chandler AB, Dinsmore RE, et al. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis: a report from the Committee on Vascular Lesions of the Council on Arteriosclerosis, American Heart Association. Arterioscler Thromb Vasc Biol 1995;15:1512–1531.[Abstract/Free Full Text]
30. Virmani R, Kolodgie FD, Burke AP, Farb A, Schwartz SM. Lessons from sudden coronary death: a comprehensive morphological classification scheme for atherosclerotic lesions. Arterioscler Thromb Vasc Biol 2000;20:1262–1275.[Free Full Text]
31. Barrett JF, Keat N. Artifacts in CT: recognition and avoidance. RadioGraphics 2004;24:1679–1691.[Abstract/Free Full Text]
32. Stary HC. Natural history and histological classification of atherosclerotic lesions: an update. Arterioscler Thromb Vasc Biol 2000;20:1177–1178.[Free Full Text]

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