Accuracy of a Novel Risk Index Combining Degree of Stenosis of the Carotid Artery and Plaque Surface Echogenicity

Abstract

Conclusion:A new ultrasound risk index parallels the presence of symptoms and may be a means of assessing the clinical risk of a carotid plaque.Summary: Thus far, prophylactic intervention for carotid artery stenosis is determined primarily by the severity of the degree of the stenosis. However, stenosis severity itself in asymptomatic patients is relatively insensitive in determining which patients develop neurologic symptoms. Additional variables, such as plaque morphology, may also play an important role in occurrence of cerebrovascular events and may be predictors of ipsilateral stoke that act independently or in concert with the degree of stenosis. The authors developed an ultrasound risk index (RI) based on the combination of degree of stenosis and echogenicity of the plaque surface. In this study, the aim was to evaluate the accuracy of the RI in a cohort of consecutive patients presenting with symptomatic or asymptomatic carotid stenosis. In addition, the authors wished to compare this method with other wellestablished parameters, including degree of stenosis alone and gray-scale median of the plaque, for predicting potential neurologic events associated with carotid stenosis. The authors used consecutive patients with 50% to 99% internal carotid stenosis. Semi-automated gray scale-based color mapping (red, yellow, and green) of the whole plaque and of its surface was preformed. The surface was defined as the region located between the lumen (level 0) and, respectively, 0.5, 1, 1.5, and 2 mm below the surface. RI was based on the combination of the degree of stenosis and the proportion of red color (indicating low echogenicity) on the surface or in the whole plaque. There were 67 symptomatic and 117 asymptomatic carotid stenoses analyzed. RI values were higher among symptomatic lesions (0.46 vs 0.29; P Ͻ .001). Using receiver operating characteristic curves, RI had stronger predictive value compared with degree of stenosis or surface echogenicity alone. In a regression model that included age, gender, degree of stenosis, surface echogenicity, gray-scale median of the whole plaque, and RI, RI measured within the surface region (0.5 mm from the lumen) was the only parameter significantly associated with the presence of symptoms (odds ratio, 4.89; 95% confidence interval, 2.7-8.7; P ϭ .0000002). RI was also the best criteria to differentiate between symptomatic and asymptomatic stenosis (RI value Ͻ0.36, sensitivity 78% and specificity 65%).Comment: These authors studied many different parameters to predict symptoms associated with carotid plaque, including age, gender, degree of stenosis, surface echogenicity, gray-scale median of the whole plaque, and RI. Of all these parameters, it is intriguing that only RI measured within the surface region located 0.5 mm from the lumen was significantly associated with the presence of symptoms. Unfortunately, the authors' RI, while an intriguing new ultrasound parameter, appears somewhat difficult to calculate, and it is unknown if the data are reproducible among differ...

A Novel Ultrasound-Based Carotid Plaque Risk Index Associated with the Presence of Cerebrovascular Symptoms

“…Our study has found that a new, intuitive model that does not have any parameters which are optimized for our data has better diagnostic performance than DOS and a dataset-optimized risk index. The area under the ROC curve (0.849 for CPRI vs. 0.771 for DOS and 0.845 for CPRI logistic ) compared favorably with that of the more complicated, dataset-optimized risk index defined by Momjian-Mayor et al [24]. This model has the additional benefit that it may be employed by different centers without re-optimization of the weighting factors.…”

“…Two-tailed tests of significance were used and p-values less than 0.05 were considered statistically significant. A carotid plaque risk index based on logistic regression methods (CPRI logistic ) was constructed, similar to Momjian-Mayor et al [24] in the form of 1/(1 + exp(-x)) where x is equal to β0 + β1*DOS + β2*GSM + β3*SII and β0, β1, β2, β3 are factors that are optimized for the data. Our CPRI, on the other hand, was defined as (DOS*SII)/(GSM + 1) with no dataset-optimized parameters.…”

“…Prati et al defined a risk index incorporating DOS, and qualitative measures of surface irregularities, plaque echogenicity and texture [23]. Momjian-Mayor et al defined a risk index combining DOS with a quantitative measure of the plaque surface echogenicity and used a logistic regression-based statistical model with weighting factors optimized for their dataset [24]. Pedro et al similarly developed an activity index, comprising several measures including that of plaque surface disruption (qualitative assessment), GSM, percentage of plaque area with gray levels less than 40, plaque heterogeneity (qualitative assessment), and the presence of juxta-luminal echolucent areas (qualitative assessment), in addition to DOS.…”

“…Obtaining good classification accuracy need not mean the model is generally valid, if the model includes parameters that have been optimized for the dataset method of assessment used. The incorporation of qualitative measures into some risk models can also be considered a separate limitation since intra-and inter-observer agreement can be low for such subjective assessments [24,29]. Another group of studies have attempted to classify plaques using methods such as pattern recognition, neural networks, support vector machines, and other machine learning algorithms but these do not provide risk indices and suffer from the same limitations [32 -39].…”

Echographic Risk Index and Cerebral Ischemic Brain Lesions in Patients Randomized to Stenting versus Endarterectomy for Symptomatic Carotid Artery Stenosis

“…Reduced plaque echogenicity on duplex ultrasound Bmode images (plaque echolucency) corresponds to histological markers of plaque instability [7,8] and is associated with an increased risk of stroke [8 -13]. More recently, an Echographic Risk Index (ERI) based on a combination of degree of stenosis and proportion of echolucent area at the plaque surface has been demonstrated to predict symptom status and presence of ipsilateral ischemic lesions on magnetic resonance imaging (MRI) [14]. Quantitative assessment of plaque ultrasound therefore has the potential to identify "unstable" plaques which are more likely to cause cerebrovascular events or subclinical embolization.…”