Carotid artery wall thickness measured using CT: inter- and intraobserver agreement analysis

CT of the Neck: Image Analysis and Reporting in the Emergency Setting

Interpreting findings seen at CT of the neck is challenging owing to the complex and nuanced anatomy of the neck, which contains multiple organ systems in a relatively small area. In the emergency department setting, CT is performed to investigate acute infectious or inflammatory symptoms and chronic processes. With few exceptions, neck CT should be performed with intravenous contrast material, which accentuates abnormally enhancing phlegmonous and neoplastic tissues and can be used to delineate any abscesses or necrotic areas. As part of the evaluation, the vascular structures and aerodigestive tract must be scrutinized, particularly for patency. Furthermore, although the patient may present because of symptoms that suggest non-life-threatening conditions involving structures such as the teeth or salivary glands, there may be serious implications for other areas, such as the orbits, brain, and spinal cord, that also may be revealed at the examination. With a focus on the emergency setting, the authors propose using an approach to interpreting neck CT findings whereby 12 areas are systematically evaluated and reported on: the cutaneous and subcutaneous soft tissues, aerodigestive tract and adjacent soft tissues, teeth and periodontal tissues, thyroid gland, salivary glands, lymph nodes, vascular structures, bony airspaces, cervical spine, orbits and imaged brain, lung apices, and superior mediastinum. The use of a systematic approach to interpreting neck CT findings is essential for identifying all salient findings, recognizing and synthesizing the implications of these findings to formulate the correct diagnosis, and reporting the findings and impressions in a complete, clear, and logical manner.Online supplemental material is available for this article.^©RSNA, 2019.

Nonstenotic carotid plaque on CT angiography in patients with cryptogenic stroke

OBJECTIVE

To determine whether large (≥3 mm thick) but nonstenotic (<50%) carotid artery atherosclerotic plaque predominantly occurs ipsilateral rather than contralateral to cryptogenic stroke.

METHODS

This was a cross-sectional observational study. Using a stroke registry, we identified consecutive patients with anterior circulation embolic stroke of undetermined source (ESUS). Using CT angiography, we measured carotid plaque size (thickness, mm) and carotid artery stenosis (North American Symptomatic Carotid Endarterectomy Trial method) for each patient. We dichotomized plaque size at several predefined thresholds and calculated the frequency of plaque size above each threshold ipsilateral vs contralateral to stroke.

RESULTS

We included 85 patients with ESUS. Plaque with thickness ≥5 mm was present ipsilateral to stroke in 11% of patients, and contralateral in 1% (9/85 vs 1/85; p = 0.008). Plaque with thickness ≥4 mm was present ipsilateral to stroke in 19% of patients, and contralateral in 5% (16/85 vs 4/85; p = 0.002). Plaque with thickness ≥3 mm was present ipsilateral to stroke in 35% of patients, and contralateral in 15% (30/85 vs 13/85; p = 0.001). There was no difference in percentage stenosis ipsilateral vs contralateral to stroke (p = 0.98), and weak correlation between plaque size and stenosis (R(2) = 0.26, p < 0.001).

CONCLUSIONS

Large but nonstenotic carotid artery plaque is considerably more common ipsilateral than contralateral to cryptogenic stroke, suggesting that nonstenotic plaque is an underrecognized cause of stroke. We measured plaque size using CT angiography, a method that could be easily implemented in clinical practice.

Is there an association between asymmetry of carotid artery wall thickness (ACAWT) and cerebrovascular symptoms?

PURPOSE

Previous publications demonstrated that multi-detector-row computed tomography Angiography (MDCTA) can evaluate the carotid artery wall thickness (CAWT). The purpose of this work was to compare the asymmetry of CAWT between carotids in symptomatic and asymptomatic patients.

MATERIAL AND METHODS

Sixty consecutive symptomatic (males 44; median age 64) and 60 asymptomatic sex- and age-matched patients were analysed by using a 40-detector-row CT system. CAWT was calculated for both carotids in each patient and the ratio between the thicker CAWT and the contra-lateral was calculated to obtain the ACAWT index. Bland-Altman, logistic regression and receiver operating characteristic (ROC) curve analysis were calculated.

RESULTS

The Bland-Altman plot demonstrates a very good agreement between measurements with a mean difference value of 3.4% and 95% CI from -8% to 14.8%. The ACAWT was significantly different between symptomatic and asymptomatic patients (with a p value of 0.0001). The ROC area under the curve was 0.742 (p = 0.001). Logistic regression model indicated that ACAWT, CAWT, stenosis degree, and fatty plaques were independent variables associated with cerebrovascular symptoms (p value, respectively, 0.0108, 0.0231, 0.0002, and 0.013).

CONCLUSION

Results of our study indicated that the index of asymmetry in the CAWT might be used as a further parameter to stratify the risk of symptoms related to carotid artery.

Atherosclerotic risk stratification strategy for carotid arteries using texture-based features

Plaques in the carotid artery result in stenosis, which is one of the main causes for stroke. Patients have to be carefully selected for stenosis treatments as they carry some risk. Since patients with symptomatic plaques have greater risk for strokes, an objective classification technique that classifies the plaques into symptomatic and asymptomatic classes is needed. We present a computer aided diagnostic (CAD) based ultrasound characterization methodology (a class of Atheromatic systems) that classifies the patient into symptomatic and asymptomatic classes using two kinds of datasets: (1) plaque regions in ultrasound carotids segmented semi-automatically and (2) far wall gray-scale intima-media thickness (IMT) regions along the common carotid artery segmented automatically. For both kinds of datasets, the protocol consists of estimating texture-based features in frameworks of local binary patterns (LBP) and Law's texture energy (LTE) and applying these features for obtaining the training parameters, which are then used for classification. Our database consists of 150 asymptomatic and 196 symptomatic plaque regions and 342 IMT wall regions. When using the Atheromatic-based system on semiautomatically determined plaque regions, support vector machine (SVM) classifier was adapted with highest accuracy of 83%. The accuracy registered was 89.5% on the far wall gray-scale IMT regions when using SVM, K-nearest neighbor (KNN) or radial basis probabilistic neural network (RBPNN) classifiers. LBP/LTE-based techniques on both kinds of carotid datasets are noninvasive, fast, objective and cost-effective for plaque characterization and, hence, will add more value to the existing carotid plaque diagnostics protocol. We have also proposed an index for each type of datasets: AtheromaticPi, for carotid plaque region, and AtheromaticWi, for IMT carotid wall region, based on the combination of the respective significant features. These indices show a separation between symptomatic and asymptomatic by 4.53 units and 4.42 units, respectively, thereby supporting the texture hypothesis classification.

Association between carotid artery plaque type and cerebral microbleeds

BACKGROUND AND PURPOSE

CMBs have become increasingly recognized with the widespread use of MR imaging techniques that are sensitive to iron deposits. The purpose of this study was to correlate the presence of CMBs and carotid plaque characteristics.

MATERIAL AND METHODS

Seventy consecutive patients (47 men; 23 women; mean age, 65 years) were prospectively analyzed. Carotid arteries were studied using a 16-detector row CT scanner, whereas the brain was explored with an MR imaging 1.5T system. CMBs were studied using a T2*-weighted GRE sequence. CMBs were classified by an ordinal scale and carotid plaques were characterized based on their composition as fatty, mixed, or calcified. Patients were classified as symptomatic and asymptomatic. Chi-square and multiple logistic regression analyses, as well as ROCs, were calculated.

RESULTS

The prevalence of CMBs was 30%. A statistically significant difference in CMB prevalence was observed between symptomatic (46%) and asymptomatic (19%) patients (P value = .0021; OR = 3.7). Correlation analysis demonstrated an association between the number of CMBs and the symptoms (P = .0001). A statistically significant association was observed between the presence of fatty plaque and CMBs (P = .0019).

CONCLUSIONS

The results of this study suggest an association between the presence of carotid artery fatty plaque, symptoms, and CMBs. Moreover, we found that the presence (and entity) of CMBs may represent an indicator of cerebrovascular symptom severity.