Stenosis Asymmetry Index (SAI) between symptomatic and asymptomatic patients in the analysis of carotid arteries. A study using CT angiography

Eur J Radiol. 2012 Jan;81(1):77-82. doi: 10.1016/j.ejrad.2010.12.014. Epub 2011 Jan 15.

Abstract

Purpose: 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.

Materials and methods: 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: 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%.

Conclusion: Results of our study suggest that a SAI>1.8 has a good sensitivity in identifying the association with cerebrovascular events.

Publication types

  • Comparative Study

MeSH terms

  • Adult
  • Aged
  • Algorithms*
  • Angiography / methods*
  • Carotid Stenosis / diagnostic imaging*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Severity of Illness Index*
  • Tomography, X-Ray Computed / methods*