Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • Advancing NeuroMRI with High-Relaxivity Contrast Agents
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • Advancing NeuroMRI with High-Relaxivity Contrast Agents
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates


Improved Turnaround Times | Median time to first decision: 12 days

Research ArticleHead and Neck Imaging

Significance of Sonographic Tissue and Surface Characteristics of Carotid Plaques

Thomas J. Tegos, Konstantinos J. Kalomiris, Michael M. Sabetai, Evi Kalodiki and Andrew N. Nicolaides
American Journal of Neuroradiology September 2001, 22 (8) 1605-1612;
Thomas J. Tegos
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Konstantinos J. Kalomiris
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael M. Sabetai
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Evi Kalodiki
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrew N. Nicolaides
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

Abstract

BACKGROUND AND PURPOSE: Our hypothesis was that symptomatic and asymptomatic carotid plaques are different. The aim of this study was to identify the sonographic tissue and surface characteristics of plaques and their degree of stenosis that corresponded to these two clinical presentations.

METHODS: We studied 81 symptomatic and 111 asymptomatic plaques (150 patients) having 50% to 99% stenosis on duplex scanning. These plaques were imaged on duplex and captured in a computer. We evaluated the gray-scale median (GSM) to distinguish hypoechoic (low GSM) from hyperechoic (high GSM) plaques, and the bending energy (BE), to distinguish plaques with irregular (high BE) versus smooth (low BE) surfaces.

RESULTS: The symptomatic group corresponded to hypoechoic (median GSM, 4) and severely stenosed (median stenosis, 85%) plaques, whereas the asymptomatic group corresponded to hyperechoic (median GSM, 35) and moderately stenosed (median stenosis, 70%) plaques (P < .05 for both variables). The BE failed to separate the two groups; the mean BEs were 1.63 and 1.68 for the symptomatic and asymptomatic groups, respectively (P = .38).

CONCLUSION: Our results suggest that echogenic characteristics and the degree of stenosis are the strongest predictors of carotid plaque behavior. The sonographic surface characteristics failed to qualify as an index of plaque instability.

A longitudinal study of asymptomatic patients with carotid atheroma has shown that the hypoechoic and severely stenosed plaques are associated with a higher rate of an incident stroke (1). This observation stresses the importance of the echogenic characteristics and stenosis of the carotid atheroma in the pathogenesis of stroke.

In addition, a previous study has shown that hypoechoic and ulcerated carotid plaques on sonograms are associated with neurovascular symptoms, whereas hyperechoic and smooth-surfaced plaques are associated with an asymptomatic status (2). This study stresses the importance of sonographic ulcerations in the development of neurovascular symptoms. The plaque features, however, were visually evaluated and therefore not extremely accurate.

The aim of this cross-sectional study was to determine 1) computer-evaluated attributes of carotid plaques (in terms of sonographic tissue and surface characteristics) and 2) the degree of stenosis associated with the presence of neurovascular symptoms. It was hoped that the recognition of these features might elucidate the pathophysiological mechanisms involved.

Methods

We studied 192 carotid bifurcation plaques (from 95 men and 55 women; mean age, 70.32 years; range, 42 to 92 years), producing stenosis in the range of 50% to 99% at duplex scanning. These plaques were associated with no symptoms (n = 111, 57.8%), amaurosis fugax (n = 27, 14.1%), hemispheric transient ischemic attack (n = 35, 18.2%), or stroke (n = 19, 9.9%) on the retinal or hemispheric side ipsilateral to the plaque. Each plaque with its ipsilateral retinal or hemispheric side was treated as an independent case (unit of the study) and defined the side of interest on each patient. In all, 108 patients had unilateral carotid atheromas and 42 had bilateral carotid atheromas that could be analyzed.

Patients were recruited during duplex scanning in our vascular laboratory, and we relied upon referrals from medical, neurologic, and vascular surgical clinics. The reason for referral was to investigate the carotid arteries because of either a neurovascular symptom (symptomatic patients) or a carotid bruit with no symptoms (asymptomatic patients). The sonographic tissue and surface characteristics and stenosis of the carotid plaques were evaluated on presentation; duplex scanning is part of the routine investigation of patients with carotid atheromas in our hospital.

Symptoms were assigned by a neurologist who was unaware of the previous clinical reports and duplex findings, in accordance with the recommendations of the Committee for the Classification of Cerebrovascular Disease III (3). Appropriate to the concept of a cross-sectional investigation, we noted neurovascular symptoms only within the last 6 months on the side of interest (>50% stenosis). Patients with symptoms on the appropriate side more than 6 months before recruitment were excluded. This exclusion criterion was based on the fact that a plaque may change in terms of stenosis, surface, and echogenicity characteristics over time. In the present study, the intention was to “incriminate” the plaque under investigation in the development of symptoms.

Asymptomatic patients were considered those who had never had symptoms on the side of interest. Symptoms on the sides with <50% stenosis and in the vertebrobasilar system were not analyzed. The rationale for the exclusion of plaques producing <50% stenosis was based on the fact that it is more probable for a symptom caused by a carotid atheroma to be ascribed to a stenosis >50%, as suggested by the North American Symptomatic Carotid Endarterectomy Trial collaborators (4).

Patients with cardioembolic conditions such as atrial fibrillation, aortic or mitral valve abnormalities, recent (<6 weeks before the neurovascular event) myocardial infarction, or prosthetic cardiac valves and heart failure were excluded by a cardiologist on clinical and electrocardiographic grounds (3). Additional exclusion criteria included lacunar symptoms (pure motor hemiparesis, pure sensory stroke, motor-sensory stroke, ataxic hemiparesis, dysarthria clumsy-hand syndrome, and absence of cortical dysfunction) and cerebral hemorrhage, diagnosed by a neurologist on clinical and brain CT grounds (3), because lacunae and cerebral hemorrhages are not attributable to carotid atheroma.

These criteria (>50% carotid stenosis and exclusion of cardioembolism, lacunar symptoms, and cerebral hemorrhage) ensured the implication of carotid atheroma as the most likely cause in the pathogenesis of the neurovascular symptoms. The patients (n = 150) were selected from a total of 811 consecutive patients whose carotid stenosis was evaluated in our laboratory from July 1998 to December 1998.

Sonographic Evaluation: Grading of Internal Carotid Artery Stenosis

The severity of carotid stenosis was assessed at duplex scanning upon recruitment, using an ATL HDI 3000 scanner (Advanced Technology Laboratories, Bothell, Washington, USA). This entailed a hemodynamic evaluation of the index stenotic vessel based on standard criteria (Table 1) (5–12). The evaluation was performed by one experienced operator (T.J.T.) who was unaware of the clinical profile of the patients at the time of scanning and was fully familiar with the protocol of the grading of carotid stenosis.

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 1:

Grading of carotid stenosis

Sonographic Tissue Characteristics of Carotid Plaques

Method

The carotid plaques were scanned on the ATL HDI 3000 scanner with a 7-MHz linear probe in the longitudinal, anterolateral projection at a minimal depth, then their b-mode static images were captured (capturing device: SCREEN MACHINE II version 1.1, Fast Multimedia AG, Munich, Germany) and digitized in a computer (Dell Dimension XPS P90, Berkshire, UK), keeping standard settings (13). The scanner settings were: medium frame rate, time gain compensation vertical to the blood vessel, linear postprocessing curve, minimal persistence, and maximum dynamic range (in this material, 60 dB). For the scanning settings, the gain, magnification, and angle of projection were adjusted so that in the captured image, the blood was dark, the adventitia was horizontal and bright, and the atherosclerotic plaque was well delineated. The source settings, display settings, effect settings, color settings, and capturing resolution (736 × 560 pixels) of the grabber were fixed for image capturing.

The overall brightness of the areas under study in the digital images was evaluated by computer software (Adobe Photoshop, Adobe Systems Inc., version 3, San Jose, CA) by means of the gray-scale median (GSM). This represents the median of the frequency distribution of tones of pixels included in these areas (13). After digitization, all images were normalized with linear scaling by the software, so that the GSM of blood was 0–5 tones, and that of the adventitia, 180–200 (13). By altering the images, we counteracted the effect of the different degrees of sonographic gain on plaque echogenicity, as has been shown (14). After normalization, the overall brightness of the plaques was evaluated by means of GSM.

Plaques included in an acoustic shadow were considered echoically analyzable by echo if more than 50% of their area offered real acoustic information, and only this section was subjected to analysis (the number of pixels in the analyzable area was at least half of the overall number of pixels in the plaque image as calculated by the software) (14).

In the case of poor visualization of the luminal edge, especially in hypoechoic (dark) plaques, we studied color images in parallel to the b-mode (gray scale) images to assist in delineation of the luminal margin. Color images were frozen on the screen, and an automatic switch-off of the color in the ATL HDI 3000 scanner provided the b-mode images on the same plane) (14).

These analyses were performed on presentation by the same experienced operator (T.J.T.) who evaluated the degree of stenosis.

Quantification of Visually Evaluated Echogenicity

The overall brightness of the plaques (n = 192) was evaluated by GSM and visually by one experienced operator (T.J.T.) at different times. The visual evaluation entailed a classification of the plaques into type 1 (hypoechoic, brightness equal to that of blood), type 2 (isoechoic, brightness equal to that of the periadventitia), or type 3 (hyperechoic, brightness greater than that of the periadventitia), as suggested by Polak et al (1). The median GSMs of the three groups (as they were classified visually into types) were compared to show the correspondence of the visual and digital evaluations of plaque echogenicity.

The comparison of the three visually evaluated echogenicity groups of plaque types by terms of GSM showed their separability (median GSM for type 1, 0; interquartile range, 0; median GSM for type 2, 15; interquartile range, 30; median GSM for type 3, 63; interquartile range, 30.5; Kruskal-Wallis test, P = .001 [Fig 1]). The use of medians, interquartile ranges, and nonparametric statistics was justified because the distribution of GSM was nonnormal (one-sample Kolmogorov-Smirnov test, P = .001).

fig 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
fig 1.

Comparison of the three visually evaluated echogenicity groups of plaques (types 1, 2, and 3) in terms of GSM.fig 2. Interoperator reproducibility of the BE evaluation.fig 3. Intraoperator reproducibility of the BE evaluationfig 4. An intermediate hypoechoic (GSM, 17) and smooth (BE, 0.32) plaque.fig 5. An intermediate hyperechoic (GSM, 48) and intermediately irregularly surfaced (BE, 1.5) plaque.fig 6. Comparison of the three visually evaluated echo-surface groups of the plaques (types 1, 2, and 3) in terms of BE

Interoperator Reproducibility of Echogenecity by Visual Evaluation

The overall brightness of plaques (n = 192) was evaluated visually by two independent, experienced operators, and the interoperator reproducibility was calculated. The visual evaluation entailed a classification of the plaques into the three types described above (1). The results of the interoperator reproducibility were satisfactory (κ = .95; SE, .018; 95% confidence interval, .92–.99 [Table 2]).

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 2:

Interoperator reproducibility, visual evaluation of plaque echogenicity

Sonographic Surface Characteristics of Carotid Plaques

Method

The sonographic surface characteristics of the digital plaque images were evaluated in the same computer by means of the bending energy (BE) and by the same experienced operator (T.J.T.) who evaluated the plaque echogenicity. The BE is a feature that measures the irregularity of a digital curve and can be perceived as the energy necessary to bend a rod to a desired shape (15). In this study, the BE described the irregularity of the luminal edge of the plaques (irregular or smooth) and was the output of computer software.

The evaluation of BE is based on a semiautomated method. Initially, the operator tracked the luminal edges of the plaques in the digital b-mode images by points and the program smoothed the resultant lines by interpolation. Then, the program identified the pixels corresponding to these lines and produced arrays of pixels. In the next step, the program produced arrays of numbers describing the relative position of every pixel to the following one, starting from the left side of the lines. For example, pairs of neighboring pixels being side by side corresponded to different numbers compared with those placed diagonally at 45° or 225°, one above the other or one below the other. These numbers described the rate of angulation of the lines under study and discriminated straight from curved lines. The end product was the evaluation of curvature vectors and finally of BEs.

The analysis was performed on b-mode images by using as a guide the color images for the identification of the luminal plaque edges. The color images were frozen on the screen, and an automatic switch-off of the color in the ATL HDI 3000 scanner provided the b-mode images on the same plane. These were the same images used for the evaluation of echogenicity.

Interoperator and Intraoperator Reproducibility of BE

The BE of 89 plaques was evaluated in a computer by two independent, experienced operators. The one-sample Kolmogorov-Smirnov test was performed on both distributions of BE and showed normality (first operator, P = .88; second operator, P = .39). This result dictated the use of a parametric test in the analysis of the BE.

The comparison of the two operators in terms of BE, taking into account the within-plaque variability, showed that these two groups were similar in terms of their BE means (mean ± SD 1.8 ± .5 for the first operator vs 1.76 ± .44 for the second; Fig 2). A univariate analysis of variance, with a fixed-effect model and two-way analysis yielded a P value of .68.

The BE of 21 plaques was evaluated in a computer by one experienced operator (T.J.T.) at two different times. The one-sample Kolmogorov-Smirnov test performed on both distributions of BE showed normality (first evaluation, P = .72; second evaluation, P = .88). This result dictated the use of a parametric test in the analysis of the BE.

Comparison of the two evaluations of BE, taking into account the within-plaque variability, showed that these two groups were similar in terms of their BE means (mean ± SD 1.85 ± .69 for the first evaluation and 1.82 ± .57 for the second; Fig 3). Univariate analysis of variance with a fixed effect model, two-way analysis, yielded a P value of .4.

Quantification of Visually Evaluated Surface Characteristics

The surface characteristics of the plaques (n = 89) were evaluated visually and by BE by one experienced operator (T.J.T.) at different time frames. The visual evaluation entailed classification of the plaques into type 1 (smooth surface), type 2 (intermediately irregular surface), or type 3 (completely irregular surface [Figs 4 and 5]). The means and standard deviations of the three groups (as they were classified visually into the three types) were compared to show the correspondence of the visual and digital evaluations of plaque echo-surface.

The comparison of the three visually evaluated echo-surface groups of plaque types by means of BE showed their separability (mean BE for type 1, 1.14 ± .22; for type 2, 1.98 ± .43; for type 3, 1.84 ± .33; one-way analysis of variance, P = .0001, [Fig 6]). The use of means, standard deviations, and parametric statistics was justified because the distribution of BE was normal (one-sample Kolmogorov-Smirnov test, P = .88).

Interoperator Reproducibility of Echo Surface by Visual Evaluation

The irregularity of the luminal surface of 89 plaques was evaluated visually by two independent, experienced operators, and the interoperator reproducibility was calculated. The visual evaluation again entailed a classification of the plaques into the three types. The interoperator reproducibility (Table 3) showed satisfactory results (κ = .72; SE, .075, 95% confidence interval, .57–.86).

View this table:
  • View inline
  • View popup
  • Download powerpoint
TABLE 3:

Interoperator reproducibility, visual evaluation of plaque echo-surface characteristics

Statistical Analysis

The statistical package SPSS for Windows, release 9, was used for data analysis. The one-sample Kolmogorov-Smirnov test was used to evaluate the normality of the distributions (GSM, ipsilateral stenosis, and BE). The Mann-Whitney U test and the unpaired t test were performed to distinguish the plaques associated with symptomatic and asymptomatic sides, in terms of GSM, ipsilateral stenosis, and BE. Binary logistic regression was performed to assess the value of each variable (GSM, ipsilateral stenosis, and BE) in the prediction of symptomatic versus asymptomatic presentation. The accepted level of statistical significance was 5%.

Results

The distribution of the clinical status of the 192 sides of interest included 81 symptomatic sides (42.2%, the symptomatic group) and 111 asymptomatic sides (57.8%, the asymptomatic group).

The one-sample Kolmogorov-Smirnov test performed on the distribution of the GSM showed nonnormality (P = .001), dictating the use of a nonparametric test in its analysis. The median GSM in our population was 14.5 (range, 0–98). Comparison of the distributions of the GSM between the symptomatic and asymptomatic groups showed that these groups were distinct in terms of this variable (Mann-Whitney U test, P = .001). The median GSM (interquartile range) was 4 (23.5) for the symptomatic group and 35 (55) for the asymptomatic group.

The one-sample Kolmogorov-Smirnov test was performed on the distribution of the stenosis and also showed nonnormality (P = .0001), dictating the use of a nonparametric test in the analysis of the stenosis. The median stenosis overall was 80% (range, 50–99%). The distributions of the stenosis in the symptomatic and asymptomatic groups were distinct, with median values (interquartile ranges) of 85% (20%) and 70% (25%), respectively (Mann-Whitney U test, P = .001).

The one-sample Kolmogorov-Smirnov test performed on the distribution of the BE showed normality (P = .88), dictating the use of a parametric test in the analysis of BE. The mean BE in our population was 1.66 (range, .32–3.08). The distributions of the BE were similar between the two groups, with means (±SD) of 1.63 ± .38 for the symptomatic group and 1.68 ± .43 for the asymptomatic group (unpaired t test, P = .39).

Binary logistic regression (enter method) considering the GSM, ipsilateral stenosis, and BE as independent variables and the presence or absence of neurovascular symptoms as the dependent variable showed the strongest predictors of symptoms to be the GSM (P = .001; regression coefficient, .02; odds ratio, 1.03; 95% confidence interval, 1.01–1.04) and stenosis (P = .001; regression coefficient, −.03; odds ratio, .96; 95% confidence interval, .94–.98). The BE was not a predictor of neurovascular symptoms (P = .51; regression coefficient, .25; odds ratio, 1.28; 95% confidence interval, .6–2.74).

The GSM and stenosis were slightly related in an inverse linear fashion (Pearson's correlation, P = .001, r = -.24), whereas these features were linearly unrelated to the BE (Pearson's correlation for the GSM-BE correlation, P = .26; r = .08; for the stenosis-BE correlation, P = .8; r = .01).

Discussion

Previous studies have shown that dark sonographic tissue characteristics (hypoechogenicity), severe stenosis, and the presence of an “sonographic” ulcer indicate an unstable (symptomatic) carotid plaque (1, 2, 16). The present study was conducted in attempt to identify the strongest determinants of plaque instability. In the current study, the GSM and the degree of carotid stenosis were the discriminators between the symptomatic and asymptomatic groups. The BE failed to qualify as a discriminator.

The current study showed excellent interoperator reproducibility of the visually evaluated plaque echogenic patterns, according to the three-type classification system proposed by Polak et al (1) (κ value of agreement, .95). It also showed the adequacy of the GSM to assess these patterns quantitatively.

Arnold et al (17), using a four-type classification system for echogenicity (Gray-Weale; type 1, hypoechoic plaques, to type 4, hyperechoic plaques), showed κ values of .53 for the intraoperator reproducibility and .52 for the interoperator reproducibility in an off-line image analysis (18). One possible reason for the low κ values is that the reproducibility studies were performed on nonstandardized (nonnormalized) images. In an on-line image analysis, Mathiesen et al showed a κ value of .56 for the interoperator reproducibility of plaque echogenicity using the Gray-Weale classification (19). In this study, there was no provision for the sonographic gain standardization and the angle of interrogation of plaques. Geroulakos et al (20) showed a κ value for interoperator reproducibility of .79 in an off-line analysis of plaque echogenicity, using a five-type classification system and strict scan settings. Possibly, the photographic paper they used for image storage, with the compression it produces, contributed to this result. Joakimsen et al (21), in an off-line analysis using the Gray-Weale classification and following strict criteria for the sonographic settings, gain standardization, and two echoanatomic reference points (blood and adventitia) for evaluation of plaque echogenicity, showed a κ value of .73 for interoperator reproducibility and .69 for intraoperator reproducibility. The present study showed a κ value of .95 for interoperator reproducibility. One possible explanation is the use of a three-type classification system for plaque echogenicity (as opposed to the four- or five-type classification systems) and the normalization of images that makes them more correctly classifiable by the human eye.

Regarding the evaluation of echogenic characteristics of plaques by means of GSM, the present study was based on a published method (13) that showed a satisfactory interoperator reproducibility, and its implementation of this method reduced variability in carotid plaque echogenicity when four different sonographic gains and two different scanners were used (14).

Aly and Bishop (22) used the mean of the gray scale to assess the plaque echogenicity. In the present study, the GSM was preferred because the distributions of the gray tones of the pixels in most plaque images were nonnormal. Another study used the integrated backscatter, the frequency dependence of backscatter, the integrated attenuation, and the slope of attenuation (23).

Our study also showed satisfactory interoperator reproducibility of the visually evaluated plaque echo-surface patterns. We noted satisfactory intra- and interoperator reproducibility in the evaluation of BE and adequacy of this feature to assess plaque echo-surface patterns quantitatively.

Many studies have addressed the significance of carotid plaque echogenicity in the development of neurovascular symptoms. On the basis of the Gray-Weale classification (17), various cross-sectional investigations have shown that the relative frequency of neurovascular symptoms is higher in patients with type 1 or 2 carotid plaques, whereas the frequency of asymptomatic status is higher in patients with type 3 or 4 plaques (20, 24, 25). This pattern was negated in one study, probably because of the absence of sonographic gain standardization (26).

In the pursuit of higher accuracy, El-Barghouty et al (27) used the GSM (a feature of an echo-analysis computer program) as an index of overall plaque brightness. In one cross-sectional study, they showed that carotid plaques with a low GSM (hypoechoic) were associated with a higher relative frequency of neurovascular symptoms than that of plaques with a high GSM (hyperechoic). Pedro et al (28) reached the same conclusion.

This association between the dark sonographic tissue characteristics and neurovascular symptoms has been verified in prospective, natural history studies of asymptomatic patients with carotid plaques that have used as an endpoint the development of neurovascular events. Hypoechoic plaques were symptom-prone compared with hyperechoic ones (1, 29, 30). The findings in all the above studies are in agreement with our results.

Several follow-up studies have addressed the significance of stenosis in the development of subsequent stroke. The greater the carotid stenosis, the higher the incidence of stroke, in both symptomatic and asymptomatic cohorts (1, 4, 30–32). Again, all of their findings agree with our results.

As for the significance of the carotid plaque ulceration, a series of pathologic studies has shown that this feature is associated with the development of neurovascular symptoms, possibly through embolism (33–38). A previous study, however, contradicts this position (39).

Other studies have shown that angiographically defined ulceration of carotid plaque was associated with the development of neurovascular symptoms (35, 40) or middle cerebral artery occlusion (41). In addition, a few angiographic studies have shown that “deep” ulcers (type B) or complicated, cavernous ulcers (type C) are associated with a higher incidence of neurovascular symptoms compared with “shallow” ulcers (type A) (42, 43). This angiographic classification of ulcers based on their size was proposed by Moore et al (42). Other studies have disagreed with these findings, however (44, 45).

Regarding the “sonographic” ulcer, one study showed it to be associated with the presence of neurovascular symptoms and plaque smoothness to be associated with asymptomatic status (46). Other sonographic studies have shown that it is the deep ulcer and not the surface irregularity of plaques that is associated with the presence of symptoms (2, 47). In addition, a similar study showed that irregularly surfaced plaques on sonograms were more likely to be associated with territorial brain CT infarctions than were the smooth plaques (48). The present study failed to discriminate the symptomatic and asymptomatic groups based on the digitally evaluated, sonographic surface irregularity of plaques.

The ability of angiography to identify carotid plaque ulcers verified at pathologic examination varies from poor (49, 50) to satisfactory (35, 51). In addition, sonography has proved to be poor in identifying ulcers detected at pathologic examination (52–56). This might be why our study failed to discriminate the symptomatic and asymptomatic groups on the basis of BE.

In two studies, sonography was superior to angiography in the detection of ulcerated carotid plaques identified by pathologic examination (57, 58), whereas neither method was satisfactory in another study (59).

Our study has shown that the carotid plaque GSM and stenosis are slightly related in an inverse, linear fashion. The findings of a previous study supports this result (25).

The current study showed no correlation between the carotid plaque GSM and BE. Other studies, however, have shown that hypoechoic plaques were associated with “pathologic” ulcers (17) or “sonographic” ulcers (60).

Although we noted no correlation between carotid stenosis and BE, other studies have reported that increasing degrees of carotid stenosis are associated with a high prevalence of “sonographic” ulcers (61) or “pathologic” ulcers (62). One study that evaluated the ulcers sonographically, however, found no such relationship (63), and another found that increasing degrees of carotid stenosis were not associated with angiographically verified ulcers (64).

We noted an association between carotid plaque hypoechogenicity and the development of neurovascular symptoms. In some previous studies, carotid plaque hypoechogenicity has been directly associated with the size of lipid core and inversely associated with the fibrous tissue and calcification as evaluated at pathologic examination (65–67), but not in all (68). Similarly, hemorrhage has (13) and has not (56) been associated with carotid plaque hypoechogenicity. In addition, decreased contrast of the sonographic images of carotid plaque (an index of hypoechogenicity) was found to be associated with soft material (lipids and hemorrhage) (69).

Gronholdt et al (66) hypothesized that the increased size of the lipid core (a determinant of the carotid plaque hypoechogenicity) predisposes to plaque rupture, embolism, and the development of neurovascular symptoms. Indeed, one study has reported a relationship between carotid plaque hypoechogenicity and high embolic count detected in the ipsilateral middle cerebral artery at transcranial Doppler (70).

Our study showed that severe carotid stenosis is associated with the development of neurovascular symptoms but failed to distinguish symptomatic from asymptomatic carotid plaques on the basis of the sonographic surface characteristics. This might reflect the inability of sonography to depict “real” ulcers.

Conclusion

In this study, the echogenic characteristics and degree of stenosis were the strongest predictors of carotid plaque behavior. Sonographic surface characteristics failed to qualify as an index of plaque activity.

It might be interesting to apply these methods—carotid plaque echogenicity and degree of stenosis to prospective natural-history studies of asymptomatic patients with carotid plaques, with the end point of stroke development attributable to carotid atheroma (71). Such studies might identify groups of patients at different risk for stroke. The result will be better refinement of the criteria for carotid endarterectomy, which will offer benefits both to vascular specialists and to patients.

Footnotes

  • 1 Address reprint requests to Dr. T. J. Tegos, Neurology Department, Hammersmith Hospital, 150 Du Cane Road, London W12 0HS, UK.

References

  1. ↵
    Polak JF, Shemanski L, O'Leary DH, et al. Hypoechoic plaque at US of the carotid artery: an independent risk factor for incident stroke in adults 65 years or older. (erratum published in Radiology 1998;209:288) Radiology 1998;208:649-654
    PubMed
  2. ↵
    Steinke W, Hennerici M, Rautenberg W, Mohr JP. Symptomatic and asymptomatic high-grade carotid stenoses in Doppler color-flow imaging. Neurology 1992;42:131-138
    Abstract/FREE Full Text
  3. ↵
    Steinke W, Special report from the National Institute of the Neurological Disorders and Stroke: Classification of Cerebrovascular Disease III. Stroke 1990;21:637-676
    FREE Full Text
  4. ↵
    North American Symptomatic Carotid Endarterectomy Trial Collaborators. Benefit of carotid endarterectomy in patients with symptomatic moderate or severe stenosis. N Engl J Med 1998;339:1415-1425
    CrossRefPubMed
  5. ↵
    Polak JF, Dopkin GR, O'Leary DH, Wang AM, Cutler SS. Internal carotid artery stenosis: accuracy and reproducibility of color-Doppler-assisted imaging. Radiology 1989;173:793-798
    PubMed
  6. Moneta GL, Edwards JM, Papanicolaou G, et al. Screening for asymptomatic carotid artery stenosis: duplex criteria for discriminating 60% to 99% stenosis. J Vasc Surg 1995;21:989-994
    CrossRefPubMed
  7. Hood DB, Mattos MA, Mansour A, et al. Prospective evaluation of new duplex criteria to identify 70% internal carotid artery stenosis. J Vasc Surg 1996;23:254-262
    CrossRefPubMed
  8. Withers CE, Gosink BB, Keighhtley AM, et al. Duplex carotid sonography: peak systolic velocity in quantifying internal carotid artery stenosis. J Ultrasound Med 1990;9:345-349
    Abstract
  9. Moneta GL, Taylor DC, Zierler RE, Kazmers A, Beach K, Strandness DE. Asymptomatic high grade internal carotid artery stenosis: is stratification according to risk factors or duplex spectral analysis possible? J Vasc Surg 1989;10:475-483
    CrossRefPubMed
  10. Robinson ML, Sacks D, Perlmutter GS, Marinelli DL. Diagnostic criteria for carotid duplex sonography. AJR Am J Roentgenol 1988;151:1045-1048
    PubMed
  11. Fox JF. How to measure carotid stenosis. Radiology 1993;186:316-318
    PubMed
  12. Eliasziw M, Fox AJ, Sharpe BL, Barnett HJM. Carotid artery stenosis: external validity of the North American Carotid Endarterectomy Trial measurement method. Radiology 1997;204:229-233
    PubMed
  13. ↵
    Tegos TJ, Sohail M, Sabetai MM, et al. Echomorphologic and histopathologic characteristics of unstable carotid plaques. AJNR Am J Neuroradiol 2000;21:1937-1944
    Abstract/FREE Full Text
  14. ↵
    Tegos TJ, Sabetai MM, Nicolaides AN, et al. Comparability of the ultrasonic tissue characteristics of carotid plaques. J Ultrasound Med 2000;19:399-407
    Abstract
  15. ↵
    Sonka M, Hlavac V, Boyle R. Image Processing, Analysis and Machine Vision. London, UK: Chapman and Hall Computing; 1993:203
  16. AbuRahma AF, Covelli MA, Robinson PA, Holt SM. The role of carotid duplex ultrasound in evaluating plaque morphology: potential use in selecting patients for carotid stenting. J Endovasc Surg 1999;6:59-65
    CrossRefPubMed
  17. ↵
    Gray-Weale AC, Graham JC, Burnett JR, Byrne K, Lusby RJ. Carotid artery atheroma: comparison of preoperative B-mode ultrasound appearance with carotid endarterectomy specimen pathology. J Cardiovasc Surg 1988;29:676-681
    PubMed
  18. ↵
    Arnold JA, Modaresi KB, Thomas N, Taylor PR, Padayachee TS. Carotid plaque characterization by duplex scanning: observer error may undermine current clinical trials. Stroke 1999;30:61-65
    Abstract/FREE Full Text
  19. ↵
    Mathiesen EB, Joakimsen O, Bonaa KH. Intersonographer reproducibility and intermethod variability of ultrasound measurements of carotid artery stenosis: the Tromso Study. Cerebrovasc Dis 2000;10:207-213
    CrossRefPubMed
  20. ↵
    Geroulakos G, Ramaswami G, Nicolaides A, et al. Characterisation of symptomatic and asymptomatic carotid plaques using high-resolution real-time ultrasonography. Br J Surg 1993;80:1274-1277
    CrossRefPubMed
  21. ↵
    Joakimsen O, Bonaa KH, Stensland-Bugge E. Reproducibility of ultrasound assessment of carotid plaque occurrence, thickness, and morphology: the Tromso Study. Stroke 1997;28:2201-2207
    Abstract/FREE Full Text
  22. ↵
    Aly S, Bishop CC. An objective characterization of atherosclerotic lesion: an alternative method to identify unstable plaque. Stroke 2000;31:1921-1924
    Abstract/FREE Full Text
  23. ↵
    Bridal SL, Beyssen B, Fornes P, Julia P, Berger G. Multiparametric attenuation and backscatter images for characterization of carotid plaque. Ultrason Imaging 2000;22:20-34
    Abstract/FREE Full Text
  24. Langsfeld M, Lusby RJ. The spectrum of carotid artery disease in asymptomatic patients. J Cardiovasc Surg 1988;29:687-691
    PubMed
  25. ↵
    Holdsworth RJ, McCollum PT, Bryce JS, Harrison DK. Symptoms, stenosis and carotid plaque morphology: is plaque morphology relevant? Eur J Vasc Endovasc Surg 1995;9:80-85
    CrossRefPubMed
  26. ↵
    Hallerstam S, Carlstrom C, Zetterling M, Konrad P, Rosfors S. Carotid atherosclerosis in relation to symptoms from the territory supplied by the carotid artery. Eur J Vasc Endovasc Surg 2000;19:356-361
    CrossRefPubMed
  27. ↵
    El-Barghouty NE, Nicolaides A, Bahal V, Geroulakos G, Androulakis A. The identification of high risk carotid plaque. Eur J Vasc Endovasc Surg 1996;11:470-478
    CrossRefPubMed
  28. ↵
    Pedro LM, Pedro MM, Goncalves I, et al. Computer-assisted carotid plaque analysis: characteristics of plaques associated with cerebrovascular symptoms and cerebral infarction. Eur J Vasc Endovasc Surg 2000;19:118-123
    CrossRefPubMed
  29. Johnson JM, Kennelly MM, Decessare D, Morgan S, Sparrow A. Natural history of asymptomatic carotid plaque. Arch Surg 1985;120:1010-1012
    CrossRefPubMed
  30. Langsfeld M, Gray-Weale AC, Lusby RJ. The role of plaque morphology and diameter reduction in the development of new symptoms in asymptomatic carotid arteries. J Vasc Surg 1989;9:548-557
    CrossRefPubMed
  31. Norris JW, Zhu CZ, Bornstein NM, Chambers BR. Vascular risks of asymptomatic carotid stenosis. Stroke 1991;22:1485-1490
    Abstract/FREE Full Text
  32. Eliasziw M, Rankin RN, Fox AJ, Haynes RB, Barnett HJM. Accuracy and prognostic consequences of ultrasonography in identifying severe carotid artery stenosis. Stroke 1995;26:1747-1752
    Abstract/FREE Full Text
  33. ↵
    Reilly LM, Lusby RJ, Hughes L, Ferrell LD, Stoney RJ, Ehrenfeld WK. Carotid plaque histology using a real time ultrasonography. Am J Surg 1983;146:188-193
    CrossRefPubMed
  34. Fisher CM, Ojemann RG. Clinico-pathologic study of carotid endarterectomy plaques. Rev Neurol 1986;142:573-589
    PubMed
  35. ↵
    Ricotta JJ, Schenk EA, Ekholm SE, DeWeese JA. Angiographic and pathologic correlates in carotid artery disease. Surgery 1986;99:284-292
    PubMed
  36. Sterpetti AV, Hunter WJ, Schultz RD. Importance of ulceration of carotid plaque in determining symptoms of cerebral ischemia. J Cardiovasc Surg 1991;32:154-158
    PubMed
  37. Bassiouny HS, Sakaguchi Y, Mikucki SA, et al. Juxtalumenal location of plaque necrosis and neoformation in symptomatic carotid stenosis. J Vasc Surg 1997;26:585-594
    CrossRefPubMed
  38. Park AE, McCarthy WJ, Pearce WH, Matsumura JS, Yao JST. Carotid plaque morphology correlates with presenting symptomatology. J Vasc Surg 1998;27:872-879
    CrossRefPubMed
  39. ↵
    Imparato AM, Riles TS, Gorstein F. The carotid bifurcation plaque: pathologic findings associated with cerebral ischemia. Stroke 1979;10:238-245
    Abstract/FREE Full Text
  40. Eliasziw M, Streifler JY, Fox AJ, Hachinski VC, Ferguson GG, Barnett HJ. Significance of plaque ulceration in symptomatic patients with high-grade carotid stenosis: North American Symptomatic Carotid Endarterectomy Trial. Stroke 1994;25:304-308
    Abstract/FREE Full Text
  41. ↵
    Kishore PR, Chase NE, Kricheff II. Carotid stenosis and intracranial emboli. Radiology 1971;100:351-356
    CrossRefPubMed
  42. ↵
    Moore WS, Boren C, Malone JM, et al. Natural history of nonstenotic, asymptomatic ulcerative lesions of the carotid artery. Arch Surg 1978;113:1352-1359
    CrossRefPubMed
  43. Dixon S, Pais SO, Raviola C, et al. Natural history of nonstenotic, asymptomatic ulcerative lesions of the carotid artery: a further analysis. Arch Surg 1982;117:1493-1498
    CrossRefPubMed
  44. ↵
    Kroener JM, Dorn PL, Shoor PM, Wickbom IG, Bernstein EF. Prognosis of asymptomatic ulcerating carotid lesions. Arch Surg 1980;115:1387-1392
    CrossRefPubMed
  45. Harward TR, Kroener JM, Wickbom IG, Bernstein EF. Natural history of asymptomatic ulcerative plaques of the carotid bifurcation. Am J Surg 1983;14:208-212
  46. ↵
    Iannuzzi A, Wilcosky T, Mercuri M, Rubba P, Bryan FA, Bond MG. Ultrasonographic correlates of carotid atherosclerosis in transient ischemic attack and stroke. Stroke 1995;26:614-619
    Abstract/FREE Full Text
  47. Johnson JM, Ansel AL, Morgan S, DeCesare D. Ultrasonographic screening for evaluation and follow-up of carotid artery ulceration: a new basis for assessing risk. Am J Surg 1982;144:614-618
    CrossRefPubMed
  48. ↵
    Kessler C, von Maravic M, Bruckmann H, Kompf D. Ultrasound for the assessment of the embolic risk of carotid plaques. Acta Neurol Scand 1995;92:231-234
    PubMed
  49. ↵
    Estol C, Claasen D, Hirsch W, Wechsler L, Moossy J. Correlative angiographic and pathologic findings in the diagnosis of ulcerated plaques in the carotid artery. Arch Neurol 1991;48:692-694
    CrossRefPubMed
  50. Streifler JY, Eliasziw M, Fox AJ, et al. Angiographic detection of carotid plaque ulceration. Comparison with surgical observations in a multicenter study: North American Symptomatic Carotid Endarterectomy Trial. Stroke 1994;25:1130-1132
    Abstract/FREE Full Text
  51. Blaisdell FW, Glickman M, Trunkey DD. Proceedings: ulcerated atheroma of the carotid artery. Arch Surg 1974;108:491-496
    CrossRefPubMed
  52. ↵
    O'Leary DH, Holen J, Ricotta JJ, Roe S, Schenk EA. Carotid bifurcation disease: prediction of ulceration with B-mode US. Radiology 1987;162:523-525
    PubMed
  53. Widder B, Paulat K, Hackspacher J, et al. Morphological characterization of carotid artery stenoses by ultrasound duplex scanning. Ultrasound Med Biol 1990;16:349-354
    CrossRefPubMed
  54. Sitzer M, Muller W, Rademacher J, et al. Color-flow Doppler-assisted duplex imaging fails to detect ulceration in high-grade internal carotid artery stenosis. J Vasc Surg 1996;23:461-465
    CrossRefPubMed
  55. ↵
    Lammie GA, Wardlaw J, Allan P, Ruckley CV, Peek R, Signorini DF. What pathological components indicate carotid atheroma activity and can these be identified reliably using ultrasound? Eur J Ultrasound 2000;11:77-86
    CrossRefPubMed
  56. ↵
    Droste DW, Karl M, Bohle RM, Kaps M. Comparison of ultrasonic and histopathological features of carotid artery stenosis. Neurol Res 1997;19:380-384
    PubMed
  57. ↵
    O'Donnell TF Jr, Erdoes L, Mackey WC, et al. Correlation of B-mode ultrasound imaging and arteriography with pathologic findings at carotid endarterectomy. Arch Surg 1985;120:443-449
    CrossRefPubMed
  58. Rubin JR, Bondi JA, Rhodes RS. Duplex scanning versus conventional arteriography for the evaluation of carotid artery plaque morphology. Surgery 1987;102:749-755
    PubMed
  59. ↵
    Ricotta JJ, Bryan FA, Bond MG, et al. Multicenter validation study of real-time (B-mode) ultrasound, arteriography, and pathologic examination. J Vasc Surg 1987;6:512-520
    CrossRefPubMed
  60. ↵
    Golledge J, Cuming R, Ellis M, Davies AH, Greenhalgh RM. Carotid plaque characteristics and presenting symptom. Br J Surg 1997;84:1697-1701
    CrossRefPubMed
  61. ↵
    Polak JF, O'Leary DH, Kronmal RA, et al. Sonographic evaluation of carotid artery atherosclerosis in the elderly: relationship of disease severity to stroke and transient ischemic attack. Radiology 1993;188:363-370
    PubMed
  62. ↵
    Bassiouny HS, Davis H, Massawa N, Gewertz BL, Glagov S, Zarins CK. Critical carotid stenoses: Morphologic and chemical similarity between symptomatic and asymptomatic plaques. J Vasc Surg 1989;9:202-212
    CrossRefPubMed
  63. ↵
    Imparato AM, Riles TS, Mintzer R, Baumann G. The importance of hemorrhage in the relationship between gross morphologic characteristics and cerebral symptoms in 376 carotid artery plaques. Ann Surg 1983;197:195-203
    PubMed
  64. ↵
    Grotta JC, Bigelow RH, Hu H, Hankins L, Fields WS. The significance of carotid stenosis or ulceration. Neurology 1984;34:437-442
    Abstract/FREE Full Text
  65. ↵
    Gronholdt ML, Wiebe BM, Laursen H, Nielsen TG, Schroeder TV, Sillesen H. Lipid-rich carotid artery plaques appear echolucent on ultrasound B-mode images and may be associated with intraplaque haemorrhage. Eur J Vasc Endovasc Surg 1997;14:439-445
    CrossRefPubMed
  66. ↵
    Gronholdt ML, Nordestgaard BG, Wiebe BM, Wilhjelm JE, Sillesen H. Echo-lucency of computerized ultrasound images of carotid atherosclerotic plaques are associated with increased levels of triglyceride-rich lipoproteins as well as increased plaque lipid content. Circulation 1998;97:34-40
    Abstract/FREE Full Text
  67. Schulte-Altedorneburg G, Droste DW, Haas N, et al. Preoperative B-mode ultrasound plaque appearance compared with carotid endarterectomy specimen histology. Acta Neurol Scand 2000;101:188-194
    CrossRefPubMed
  68. ↵
    Montauban van Swijndregt AD, Elbers HR, Moll FL, de Letter J, Ackerstaff RG. Ultrasonographic characterization of carotid plaques. Ultrasound Med Biol 1998;24:489-493
    CrossRefPubMed
  69. ↵
    Wilhjelm JE, Gronholdt ML, Wiebe B, Jespersen SK, Hansen LK, Sillesen H. Quantitative analysis of ultrasound B-mode images of carotid atherosclerotic plaque: correlation with visual classification and histological examination. IEEE Trans Med Imaging 1998;17:910-922
    CrossRefPubMed
  70. ↵
    Tegos TJ, Sabetai MM, Nicolaides AN, et al. Correlates of embolic events detected by means of transcranial Doppler in patients with carotid atheroma. J Vasc Surg 2001;33:131-138
    CrossRefPubMed
  71. ↵
    Nicolaides AN. Asymptomatic carotid stenosis and risk of stroke: identification of high risk group (ACSRS). Int Angiol 1995;14:21-23
    PubMed
  • Received September 15, 2000.
  • Accepted after revision March 24, 2001.
  • Copyright © American Society of Neuroradiology
View Abstract
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 22 (8)
American Journal of Neuroradiology
Vol. 22, Issue 8
1 Sep 2001
  • Table of Contents
  • Index by author
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Significance of Sonographic Tissue and Surface Characteristics of Carotid Plaques
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
Thomas J. Tegos, Konstantinos J. Kalomiris, Michael M. Sabetai, Evi Kalodiki, Andrew N. Nicolaides
Significance of Sonographic Tissue and Surface Characteristics of Carotid Plaques
American Journal of Neuroradiology Sep 2001, 22 (8) 1605-1612;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Significance of Sonographic Tissue and Surface Characteristics of Carotid Plaques
Thomas J. Tegos, Konstantinos J. Kalomiris, Michael M. Sabetai, Evi Kalodiki, Andrew N. Nicolaides
American Journal of Neuroradiology Sep 2001, 22 (8) 1605-1612;
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Methods
    • Results
    • Discussion
    • Conclusion
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • An Ultrasonographic Multiparametric Carotid Plaque Risk Index Associated with Cerebrovascular Symptomatology: A Study Comparing Color Doppler Imaging and Contrast-Enhanced Ultrasonography
  • Inter-Rater Reliability of Carotid Atherosclerotic Plaque Quantification by 3-Dimensional Sonography
  • Chronologic Echogenicity Changes and Histologic Correlates in Experimental Blood Clots: A Serial Sonographic Study
  • Histological Assessment of 526 Symptomatic Carotid Plaques in Relation to the Nature and Timing of Ischemic Symptoms: The Oxford Plaque Study
  • Elastin and Calcium Rather Than Collagen or Lipid Content Are Associated With Echogenicity of Human Carotid Plaques
  • Relative Value of Normalized Sonographic In Vitro Analysis of Arteriosclerotic Plaques of Internal Carotid Artery
  • Quantification of the Wall Inhomogeneity in B-mode Sonographic Images of the Carotid Artery
  • Crossref
  • Google Scholar

This article has not yet been cited by articles in journals that are participating in Crossref Cited-by Linking.

More in this TOC Section

  • Diagnostic Performance of US in Neck Node NIRADS 2
  • Hydrops Herniation into the Semicircular Canals
  • ASL Sensitivity for Head and Neck Paraganglioma
Show more HEAD AND NECK IMAGING

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner
  • Book Reviews

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire