Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy.
Eur J Radiol. 2012 Jan;81(1):77-82. doi: 10.1016/j.ejrad.2010.12.014. Epub 2011 Jan 15.
Extracranial carotid artery stenosis is accepted as a significant risk factor for cerebrovascular events. The purpose of this paper was to evaluate whether the Stenosis Asymmetry Index (SAI) between carotid arteries (in symptomatic and asymptomatic patients) can be considered a further parameter in the stroke risk stratification.
60 consecutive symptomatic (males 36; median age 64) patients and 60 non symptomatic patients matched for gender and age, were analyzed using a 40-detector-row CT angiography. Each patient was analyzed by injecting 80 mL of contrast material at a 5 mL\s flow rate. Stenosis degree of 240 carotids was calculated according to NASCET method. For each patient, the ratio between the most severe stenosis and the contralateral was calculated to obtain the SAI. Multiple logistic regression analysis was performed and ROC curve was also calculated.
Results of our study indicate a mean SAI of 1.48 (± 0.35 SD) in the asymptomatic group and a mean SAI of 1.69 (± 0.53 SD) in the symptomatic group with a statistically significant difference (p value=0.0204). The multiple logistic regression analysis did not find statistically significant association between SAI and symptoms. The ROC curve analysis indicated that an SAI value of 1.8 has a specificity of 84.31% presence of cerebral symptoms whereas using a 1.2 SAI we obtained a sensitivity of 88.24%.
Results of our study suggest that a SAI>1.8 has a good sensitivity in identifying the association with cerebrovascular events.
颅外颈动脉狭窄被认为是脑血管事件的一个重要危险因素。本文旨在评估颈动脉狭窄不对称指数（SAI）在症状性和无症状性患者中是否可作为中风风险分层的进一步参数。
连续分析了 60 例有症状（男性 36 例；中位年龄 64 岁）和 60 例性别和年龄匹配的无症状患者，采用 40 排 CT 血管造影进行分析。每位患者以 5mL/s 的流速注射 80mL 造影剂。根据 NASCET 方法计算 240 条颈动脉的狭窄程度。为每位患者计算最严重狭窄与对侧狭窄的比值，以获得 SAI。进行多因素逻辑回归分析，并计算 ROC 曲线。
本研究结果表明，无症状组的平均 SAI 为 1.48（±0.35SD），而有症状组的平均 SAI 为 1.69（±0.53SD），差异有统计学意义（p 值=0.0204）。多因素逻辑回归分析未发现 SAI 与症状之间存在统计学显著关联。ROC 曲线分析表明，SAI 值为 1.8 时具有 84.31%的特异性，存在脑症状，而使用 1.2 SAI 时，我们获得了 88.24%的敏感性。
本研究结果表明，SAI>1.8 具有良好的敏感性，可以识别与脑血管事件的相关性。
