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(Stroke. 1996;27:2173-2177.)
© 1996 American Heart Association, Inc.

Articles

Ultrasound Densitometric Analysis of Carotid Plaque Composition

Pathoanatomic Correlation

Vadim Y. Beletsky, MD; Roger E. Kelley, MD; Marjorie Fowler, MD Travis Phifer, MD

the Departments of Neurology (V.Y.B., R.E.K.), Pathology (M.F.), and Surgery (T.P.), Louisiana State University Medical Center, Shreveport.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Background and Purpose The components of a carotid artery plaque might affect the risk of ipsilateral stroke. The accuracy of carotid duplex scan in assessing stroke risk reflects the experience of the scan reader. Thus, methods that can enhance ultrasonic evaluation of plaque morphology might allow a more objective means of determining carotid-mediated stroke risk.

Methods We performed densitometric analysis of B-mode images of carotid plaques in nine patients scheduled for carotid endarterectomy. All patients had preoperative duplex color imaging and cerebral arteriography. The surgical specimen was analyzed histologically to determine the plaque components (soft plaque/organized thrombus, intraplaque hemorrhage/lipid deposition, fibrosis, and calcification). The specimen findings were correlated with the densitometric measurements to determine whether the density analysis would allow a reliable determination of the plaque substratum.

Results With 1.0 as a reference point for the moving column of blood, the mean acoustic densities (±SD) were as follows: organized thrombus, 1.8±0.5; intraplaque hemorrhage/lipid deposition, 5.15±0.9; fibrosis, 9.51±2.9; and calcification, 15.5±8.6.

Conclusions We conclude that densitometric evaluation allows differentiation of the various possible components of carotid plaque. The determination of plaque composition, based on density measurement, may provide information about its potential for thromboembolization.

Key Words: carotid artery diseases • carotid endarterectomy • densitometry • diagnostic imaging • ultrasonics

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Duplex scanning of the carotid bifurcation is a reliable means of detecting carotid stenosis secondary to plaque formation. The determination of the exact degree of carotid stenosis is important for patient management,^{1 2 3 4} but the correlation of the percentage of stenosis detected by the duplex scan and that detected by cerebral arteriography is the subject of considerable dispute.^{5 6 7} Carotid plaques can be characterized as to their location, extent, contour, and composition as well as the amount of associated stenosis. Plaque associated with fresh thrombus, a hemorrhagic component, or an irregular, friable surface (ie, ulceration) is believed to be more likely to compromise the distal carotid circulation^{8 9} and more likely to be associated with symptoms of stroke.¹⁰

The degree of associated stenosis is of paramount importance, but even with mild to moderate stenosis, the more complex and irregular the plaque, the greater the likelihood of infarction.¹⁰ The European Carotid Plaque Study Group concluded that ultrasonic plaque characteristics that correlate with the histological composition of the plaque might affect decision making in reference to carotid endarterectomy in asymptomatic patients.¹¹ Studies to date have indicated that carotid plaque ulceration^{12 13 14} as well as intraplaque hemorrhage and thrombus formation^{15 16 17} is associated with an increased risk of ipsilateral stroke.

The ultrasonic imaging of plaque is highly dependent on the quality of the scanner and the experience of the technician. The presence of "soft" (ie, noncalcified) plaque as well as partially organized or fresh thrombus formation can lead to an inaccurate interpretation. Partial absence of color Doppler flow, or altered flow characteristics within the vessel lumen, suggest the presence of a soft plaque or thrombus.^{18 19 20} Despite such a criterion, the sensitivity is limited. Furthermore, there is a potential for inaccurate interpretation because of normal variations in vessel anatomy that can alter the flow characteristics despite the absence of significant stenosis.

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Ten subjects scheduled for carotid endarterectomy were consecutively assessed in a prospective fashion. In one subject we did not obtain adequate ultrasound imaging to allow image density analysis because of excessive neck thickness, and this person was excluded from our study. The degree of stenosis was based on cerebral angiographic measurements by North American Symptomatic Carotid Endarterectomy Trial criteria.²¹ The measurements obtained from cerebral angiography correlated well with measurements by carotid ultrasound scan with a variation of no more than ±10%.

We used a high-resolution Acuson 128XP10v duplex scan with color Doppler imaging in all nine preoperative studies. We obtained multiple longitudinal, oblique, and cross-sectional B-mode views for each subject to assess carotid plaque composition by evaluating sonolucent and sonodense components. For each patient, the scan that allowed optimal visualization of the plaque was chosen for density analysis. The machine settings for depth gain compensation control were set as a straight line, and the only variable was the overall gain. The initial duplex image was printed on a color Sony Mavigraph printer with 256 levels of color intensity. This image was then reconstituted with a Hewlett-Packard ScanJet scanner interfaced with Image Pro Plus (Media Cybernetics) software. This resulted in a 12 bits-per-pixel (BPP) gray scale spectrum of 4096 possible shades, which represents an expanded array of ultrasonic densities of the analyzed tissues. After registration of the brightness of each plaque component in absolute BPP numbers, the relative values were calculated for each analyzed picture, with the reference point of blood density set as 1.0. Such densitometric analysis of the B-mode images allows enhanced differentiation of plaque composition.

Each surgical specimen was obtained en bloc and then sectioned to optimize correlation with the B-mode images. The plaques were examined by our collaborating histopathologist, who was advised about the sectioning preoperatively but was blinded to the ultrasound results. Plaque components that could be distinguished histologically included densely calcified plaque, fibrosis, intraplaque hemorrhage, intraplaque fatty deposition, and organized or fresh thrombus (soft) plaque.²² Because of similar ultrasonic densities among different histological plaque components, we grouped plaque components as follows: soft plaque/organized thrombus, intraplaque hemorrhage/fatty deposition, fibrosis, and densely calcified plaque.

We also performed a densitometric analysis of the moving column of blood by incorporating the color flow images into the same density-based gray scale that was used for plaque analysis. This type of analysis might allow differentiation of high-shear versus low-shear flow patterns within the carotid bifurcation.²³

	Results

Top Abstract Introduction Subjects and Methods Results Discussion References

 
The patient profile for our nine subjects is outlined in Table 1. The mean age was 61.2 years. All but one subject was symptomatic, and the symptoms correlated with the stenotic vessel. The degree of stenosis ranged from 70% to 98% by cerebral angiography.

View this table: [in this window] [in a new window]   Table 1. Patient Profile

The relationship between ultrasonic density measurements and histological plaque composition is summarized in Table 2. In patient 1, the plaque was termed fibrovascular by the histopathologist because of a combination of fibrous (collagenous) material with a microvascular component. On average, soft plaque/organized thrombus had a lower density than intraplaque hemorrhage/fatty deposition, which in turn had a lower density than fibrosis. Not unexpectedly, calcified plaque had the highest density measurement. When these plaque components were compared with the reference value of 1.0 for the moving column of blood, the corresponding mean ratios (±SD) were as follows: 1.8±0.5:1; 5.15±0.9:1; 9.51±2.9:1; and 15.5±8.6:1. The densitometric value of the calcified component of the plaque was the most variable, and it overlapped with the acoustic density of fibrous material. In one case (patient 4, Table 2), the ultrasound examination and densitometric analysis failed to detect microscopic intraplaque hemorrhage. In another (patient 8, Table 2), the ultrasound failed to demonstrate a fatty component of the plaque as well as a microscopic hemorrhage. These were the only instances of a discrepancy between ultrasound density versus histological analysis that we observed.

View this table: [in this window] [in a new window]   Table 2. Densitometric Evaluation of Carotid Plaque Composition in Absolute (Bits-per-Pixel) and Relative Numbers

Fig 1 is a histographic presentation of densitometric analysis of a complicated plaque with an irregular surface, compatible with ulceration, and associated thrombus along with corresponding histology. The mean density of soft plaque component was calculated as 382 BPP with a corresponding blood density of 193 BPP in absolute numbers.

View larger version (280K): [in this window] [in a new window]   Figure 1. A, Density analysis of the superimposed thrombus demonstrates a higher mean value in bits-per-pixel than blood. In addition, the thrombus has a wider-density spectrum than blood. The histogram represents the brightness and contrast image characteristics as a function of the tissue density as measured by ultrasound. Each pixel represents a specific intensity of gray, based on the B-mode ultrasound characteristics. B, Correlative carotid artery B-mode scan demonstrates an ulcerated plaque and superimposed thrombus (arrow). CCA indicates common carotid artery. C, Corresponding histological cross section shows an ulcerated, hemorrhagic plaque (arrow) and overlying recent thrombus (bar=500 µm).

In Fig 2, the effect of diffuse intimal thickening of the carotid vessel wall on the density profile is illustrated. Compared with the symmetrical double-peak pattern of the normal vessel walls (panel A), there are multiple peaks and valleys within the vessel walls of the artery with diffuse intimal thickening (panel B). Corresponding B-mode scans are illustrated in Fig 3.

View larger version (23K): [in this window] [in a new window]   Figure 2. Line profile density analysis illustrates the cross-sectional density profile of a normal carotid artery (A) and a carotid artery with diffuse intimal thickening (B). The x axis represents the diameter in pixels across vessel wall from the anterior wall, through the lumen, to the posterior wall; the y axis represents the intensity of gray, ie, ultrasonic density.

View larger version (444K): [in this window] [in a new window]   Figure 3. Corresponding B-mode scans of arteries in Fig 2. A, Normal carotid artery. B, Diffuse intimal thickening with width of the analyzed sample indicated by arrows. Corresponding histological section (C) demonstrates marked intimal thickening and fibrosis (arrows) (bar=500 µm).

Reconstitution of the original color-coded Doppler flow image into a broad-spectrum gray scale also allows derivation of a blood velocity profile of the components of the moving column of blood. This analysis is representative of the different velocity components within the vessel lumen rather than the actual density of the components. The comparison of a normal (laminar) flow pattern within the vessel lumen versus a turbulent flow pattern is illustrated in Fig 4. The normal parabolic shape of the flow curve (A) is replaced by sharp fluctuations in the density profile of moving blood (B). This presumably reflects the eddying effect within a narrowed channel. The corresponding duplex scans are illustrated in Fig 5.

View larger version (15K): [in this window] [in a new window]   Figure 4. Spectrum of blood flow velocity within a normal carotid artery lumen (A) and within a stenotic vessel (B). In this case, the density of gray within the lumen indicates the spectrum of flow velocities. The x axis represents diameter in pixels across vessel wall from the anterior wall, through the lumen, to the posterior wall; the y axis represents the intensity of gray.

View larger version (252K): [in this window] [in a new window]   Figure 5. Corresponding duplex scans for Fig 4, with superimposed color Doppler image, which has been transferred into the same gray scale that is used to analyze ultrasonic plaque density. The width of an analyzed sample is indicated by arrows. A, Flow pattern within the normal carotid artery lumen. B, Turbulent flow pattern within a stenotic vessel. In this case the density of gray within the lumen indicates the spectrum of flow velocities.

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion References

 
Computer-based densitometric analysis of carotid ultrasonic images allows enhanced differentiation of plaque composition. However, the reliability of this method is very dependent on obtaining a clearly defined plaque image that allows adequate analysis. Such an image must be relatively free of acoustic shadowing caused by dense calcification of the plaque. This can be particularly difficult when there is a dense calcific plaque along the anterior vessel wall that obscures images of the posterior wall. In the process of optimizing the image of the carotid plaque, one must ensure that the gain of the image amplification is uniform or one cannot make comparisons within the image. In addition, certain plaques cannot be adequately imaged because of anatomic limitations. The variability (or spread) in the BPP numbers in our nine cases could be reflective of both the gain settings and the sampling technique. Additional analyses are necessary to determine the possible statistical significance of such a densitometric relationship. Another potential limitation is the gray scale available for the particular B-mode scanner. A 256-level gray scale, for example, may be limited in its sensitivity for the detection of subtle differences in density among plaque components. Despite such limitations, one study reported that high-resolution ultrasound was superior to routine angiography in the detection of ulceration and intraplaque hemorrhage.²⁴ Carotid B-mode scan certainly appears to be the most reliable noninvasive method for plaque characterization in vivo.

In a recent study of the circle of Willis with a 30-MHz intravascular ultrasound probe, with histological correlation, the sensitivity was 100% and the specificity 80% for calcium deposits and 83% and 75%, respectively, for fibrous tissue.²⁵ Assessment of the correlation between ultrasonic carotid plaque appearance and histological examination was recently reported by Kagawa et al.²⁶ The authors divided the plaques into seven ultrasonic categories according to sonolucent versus sonodense and homogeneous versus heterogeneous characteristics. They reported an accuracy of 93.8% for plaque characterization in the 68 vessels studied.

Digital densitometric analysis of plaque composition has been evaluated by el-Barghouty et al,²⁷ but without histological correlation. Of 148 carotid plaques analyzed, 36% were associated with ipsilateral cerebral infarction by CT brain scan. They reported a rate of infarction of 55% in association with sonolucent plaques compared with 11% seen with sonodense plaques. They concluded that computerized plaque density analysis could identify carotid plaques associated with a higher risk of cerebral infarction. Mazzone et al²⁸ differentiated "homogeneous" from "heterogeneous" plaques with similar methodology. They divided carotid plaques into three categories—soft, fibrotic, and calcific—and concluded that quantitative texture analysis is "feasible in man" and could have potential clinical application. In a radiofrequency-based ultrasound study of carotid plaque composition, the authors were able to reliably distinguish lipid, fibrotic, and calcific components based on histological correlation in 15 patients.²⁹

Based on our initial nine cases, this method appears to provide reliable information about plaque composition. This commercially available software package can be interfaced with conventional duplex scans, and such image analysis may enhance our ability to predict the risk of stroke associated with different carotid plaque subtypes. This may be especially pertinent for patients with mild to moderate carotid stenosis or those subjects who are at higher risk for carotid endarterectomy, in which case the potential benefits must clearly outweigh risks.

At the present time, we do not believe that our densitometric technique allows differentiation of intraplaque hemorrhage from fatty material, but it appears to allow reliable differentiation of soft plaque/organized thrombus from intraplaque hemorrhage or fatty material, as well as from a predominantly calcified component. We did not observe a readily discernible relationship between the plaque morphology and/or composition and the degree of turbulent flow, but this might well be related to our limited patient series.

	Acknowledgments

 
This study was supported by a Biomedical Research Foundation of Northwest Louisiana/LSU Medical Center intramural research grant.

	Footnotes

 
Reprint requests to Vadim Y. Beletsky, MD, Department of Neurology, LSU Medical Center, 501 Kings Hwy, PO Box 33932, Shreveport, LA 71130-3932. E-mail vbelet@lsumc.edu.

Received May 31, 1996; revision received September 3, 1996; accepted September 3, 1996.

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This Article Abstract Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Beletsky, V. Y. Articles by Phifer, T. Search for Related Content PubMed PubMed Citation Articles by Beletsky, V. Y. Articles by Phifer, T.