CT imaging detects markers of vulnerable carotid plaque

September 8, 2008

Stroke remains a leading cause of death in the U.S. and is the principal medical cause of long-term disability, with 780,000 new or recurrent strokes occurring annually.1 Ischemic strokes related to carotid atherosclerotic disease make up almost 30% of the total.

Stroke remains a leading cause of death in the U.S. and is the principal medical cause of long-term disability, with 780,000 new or recurrent strokes occurring annually.1 Ischemic strokes related to carotid atherosclerotic disease make up almost 30% of the total.

Luminal narrowing is the standard parameter used to report the extent and severity of carotid artery stenosis due to atherosclerosis. The widespread use of this measure is based primarily on the results of several randomized clinical trials that showed a reduction in the risk of ischemic stroke in patients with luminal stenosis of ≥50% (assessed on conventional angiograms) after carotid endarterectomy compared with medical treatment alone.2-4

While those patients with ≥ 50% carotid stenosis, however, have a higher individual risk of developing a stroke, they represent fewer than 5% of patients. Most stroke happens in patients with < 50% carotid stenosis, who represent a large proportion of the general population (70% in men and 60% in women over 64 years of age).5,6 In patients with < 50% carotid stenosis, assessment of the lumen provides limited insight into the associated risk of stroke.2

Better stratification of patients with

VULNERABLE PLAQUE



The term vulnerable plaque has been used to describe thrombosis-prone plaques that have high probability of undergoing rapid progression, with subsequent rupture and embolization, even in the absence of significant luminal narrowing.3 A number of carotid plaque morphological features have been suggested as potential markers of vulnerable plaque, and these are possibly associated with an increased risk of stroke. The most studied is common carotid artery intima-media thickness.7,8

Embolic phenomena have been associated as well with thinning and subsequent ulceration of the fibrous cap on the surface of atherosclerotic plaque, resulting in release into the parent vessel of necrotic lipoid debris from the plaque substance, especially in the case of a high plaque lipid content.4-11 Several studies have established a correlation of plaque ulceration with clinical presentation, outcome, and prognosis,12,13 whereas calcifications appear to be protective.14,15

These carotid wall features have been studied mainly using ultrasound16-33 and MRI.34-37 Although CT angiography is a well-established technique frequently used to assess the presence and degree of carotid stenosis, very few studies have evaluated characteristics of the carotid wall with CT.

Previous studies that have explored CT angiography as a method to image carotid atherosclerotic plaques were performed using older-generation single-slice CT scanners. These studies usually focused on only one component of the carotid wall, such as calcium.

CT OF CAROTID

ATHEROSCLEROTIC PLAQUES

We recently performed a prospective study to evaluate the ability of modern multislice CTA to assess the composition of carotid artery plaques, using histology as the gold standard.38 We enrolled eight patients with transient ischemic attacks scheduled to undergo carotid CTA and endarterectomy. Endarterectomy was performed according to a special en bloc technique. An ex vivo microCT study of each endarterectomy specimen was obtained, followed by histologic examination.

A systematic comparison of CTA images with histologic sections and microCT images was performed to determine the CT attenuation associated with each component of the plaques. The pathologist outlined and labeled the regions corresponding to connective tissue, lipid-rich necrotic core, hemorrhage, and calcifications on the corresponding microCT images. This allowed calculation of the average Hounsfield density of each plaque component.

A computer algorithm that was subsequently developed automatically identifies the components of the carotid atherosclerotic plaques, based on the density of each pixel. After segmenting the inner and outer contours of the carotid artery wall from the in vivo CTA data sets, this automated classifier algorithm created a color overlay that displayed the composition of the carotid wall for each CTA image (see figure). A neuroradiologist's reading of this color overlay was compared with the pathologist's interpretation of the carotid plaque characteristics within the histologic slides.

We observed an overall 72.6% agreement in carotid plaque characterization between CTA and histologic examination. Although CTA showed perfect concordance for calcifications, it had more difficulty in identifying lipid-rich necrotic core, connective tissue, and hemorrhage because of the relative overlap in their Hounsfield densities. CTA performed well, however, in detecting large lipid cores, large hemorrhages, and ulcerations, and it was also effective in measuring fibrous cap thickness.

This study provided proof of principle that the composition of atherosclerotic plaques determined by CTA accurately reflects composition of the lesion as defined by histologic examination. Compared with previous studies, this study was unique in its use of modern multislice CT scanners with rapid acquisition, no motion artifact, and better contrast profiles and enhancement. Further, automated computer analysis was used instead of observer interpretation to identify the different components of the plaque. Automated classifier algorithms, such as the one presented in this study, may improve reproducibility in characterization of plaques and may be of interest in longitudinal studies of progression of atherosclerotic disease.

CLINICAL RELEVANCE



Using the standardized computerized assessment of CTA studies described above, we performed a retrospective cross-sectional study to identify the CT features of carotid atherosclerotic plaques that are significantly associated with the occurrence of ischemic stroke.39 We identified 136 consecutive patients admitted to our emergency department who had undergone CTA to evaluate their carotid arteries. These CTA studies were processed automatically using the custom automated algorithm.

A neuroradiologist reviewed the CT studies of the brain parenchyma obtained at baseline and the brain imaging studies obtained within the first week after the baseline CT for the presence or absence of an acute infarct and its distribution (unilateral or bilateral, single or multiple vascular territories, and location of vascular

territory). The neuroradiologist also reviewed the intracranial portion of the baseline CTA of the carotid arteries for the degree of completeness of the circle of Willis. Based on the brain CT or MRI findings and the anatomy of the circle of Willis, the neuroradiologist decided whether the distribution of an acute infarct was consistent with a carotid origin.

Patients were categorized into acute carotid stroke and nonacute carotid stroke groups independent of carotid wall CT features, using the Causative Classification System for Ischemic Stroke,40 which includes the neuroradiologist's review of the imaging studies of the brain parenchyma and of the degree of carotid stenosis, and charted test results (such as ECG and Holter). Univariate followed by multivariate analyses were used to build models to differentiate between acute and nonacute carotid stroke patients (see table), and to differentiate between the infarct and unaffected sides in the acute carotid stroke patients.

We found that an increased risk of stroke was associated with an increased carotid wall volume, thinner fibrous cap, higher number of lipid clusters within the carotid wall, and location of lipid clusters closer to the lumen. The number of calcium clusters within the carotid wall was a protective factor. These observations mirror the current understanding as to how a carotid plaque might rupture and cause an embolic stroke. Embolic phenomena have been previously reported as being associated with thinning and subsequent ulceration of the fibrous cap on the surface of the atherosclerotic plaque, resulting in release of necrotic lipid debris from the plaque substance into the parent vessel, especially in the case of high lipid content.

FUTURE STEPS

The originality of our research lies in the use of CT, routinely used to evaluate the degree of luminal narrowing, to assess the carotid artery wall. In order to characterize carotid wall features other than calcium from CT data, we developed an automated classifier computer algorithm and validated it against histological examination. Our work using CT is not intended to detract from other imaging techniques.

Ultrasound is noninvasive, can be performed at bedside, and gives accurate assessment of the carotid intima-media thickness. MRI, with appro¬priate sequences, affords unmatched tissue contrast between the different plaque components. CT is obtained as part of the standard of care, however, for numerous patients with cerebro¬vascular disease, as a result of its wide availability and the short duration of CT studies.

Our results show that the interpretation of CT studies of the carotid arteries should not be limited to the evaluation of the degree of luminal narrowing but should also include assessment of the carotid wall. The automated algorithm approach af¬fords a standardized 3D volumetric assessment of the carotid artery wall. Longitudinal studies are needed to demonstrate that the carotid plaque CT features we identified (wall thickness, fibrous cap thickness, number and location of lipid clusters, and number of calcium clusters) help prospectively predict the risk of stroke and identify patients who require stenting/endarterectomy, especially among those with

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Mr. Magge is a Doris Duke medical student, Mr. Sandeep is a research fellow, Dr. Soares is a research fellow, Mr. Lau is a research assistant, Ms. Tong is a medical student, and Dr. Wintermark is an assistant professor of radiology, all in the Neuro¬CardioVascular Imaging Lab of the radiology department at the University of California, San Francisco.