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Objectives <p>The aim of our study was to evaluate the value of the fat attenuation index (FAI) as a tool for measuring plaque inflammation in perivascular adipose tissue (PVAT) and identifying symptomatic plaques in internal carotid atherosclerosis.</p> Methods <p>We conducted a retrospective analysis of patients with internal carotid atherosclerosis who underwent carotid artery computed tomography angiography (CTA). The patients were assigned to a symptomatic plaque group or asymptomatic plaque group on the basis of clinical diagnosis and neuroimaging. We measured perivascular FAIs at the maximum stenosis site with the plaque, the nonstenosis site adjacent to the maximum stenosis site, and the ipsilateral internal carotid artery (ICA). We subsequently compared these measurements between the two groups. Multivariable generalized estimating equation (GEE) analysis was performed to identify imaging predictors of symptomatic plaque in the ICA, and receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracy for classifying symptomatic plaques.</p> Results <p>A total of 101 and 94 ICAs were included in the symptomatic plaque group and asymptomatic plaque group, respectively. Mild ICA stenosis resulted in a lower FAI at the maximum stenosis site than moderate or severe stenosis did (<i>p</i> = 0.001). A greater FAI of the ipsilateral ICA was observed in the symptomatic plaque group than in the asymptomatic plaque group (<i>p</i> = 0.002), as was the FAI at the maximum stenosis site of the ICA with the plaque (<i>p</i> = 0.038). Multivariable GEE analysis revealed that the stenosis severity (<i>p</i> = 0.004) and FAI at the maximum stenosis site of the ICA (<i>p</i> = 0.007) were capable of identifying symptomatic plaques. ROC analysis revealed that the FAI at the maximum stenosis site of the ICA, in combination with stenosis severity, resulted in a higher area under the curve (AUC) value (0.863) with moderate specificity (74%) and high sensitivity (89%).</p> Conclusion <p>The perivascular FAI at the maximum stenosis site of the ICA is useful for identifying symptomatic plaques by monitoring inflammation in patients with ICA atherosclerosis, which may provide a new inflammation marker for risk stratification of patients with stroke.</p>

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Perivascular fat attenuation index at internal carotid artery stenosis: a biomarker of perivascular adipose tissue (PVAT) inflammation

  • 期刊论文

  • 发表日期：

    2025年10月8日

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  • Ziyu Tian,
  • Donglai Li,
  • Liping Zuo,
  • Shanshan Qin,
  • Zhe Tang,
  • Guang Li,
  • Shijie Deng,
  • Kai Zhang,
  • Dexin Yu

摘要

Objectives

The aim of our study was to evaluate the value of the fat attenuation index (FAI) as a tool for measuring plaque inflammation in perivascular adipose tissue (PVAT) and identifying symptomatic plaques in internal carotid atherosclerosis.

Methods

We conducted a retrospective analysis of patients with internal carotid atherosclerosis who underwent carotid artery computed tomography angiography (CTA). The patients were assigned to a symptomatic plaque group or asymptomatic plaque group on the basis of clinical diagnosis and neuroimaging. We measured perivascular FAIs at the maximum stenosis site with the plaque, the nonstenosis site adjacent to the maximum stenosis site, and the ipsilateral internal carotid artery (ICA). We subsequently compared these measurements between the two groups. Multivariable generalized estimating equation (GEE) analysis was performed to identify imaging predictors of symptomatic plaque in the ICA, and receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracy for classifying symptomatic plaques.

Results

A total of 101 and 94 ICAs were included in the symptomatic plaque group and asymptomatic plaque group, respectively. Mild ICA stenosis resulted in a lower FAI at the maximum stenosis site than moderate or severe stenosis did (p = 0.001). A greater FAI of the ipsilateral ICA was observed in the symptomatic plaque group than in the asymptomatic plaque group (p = 0.002), as was the FAI at the maximum stenosis site of the ICA with the plaque (p = 0.038). Multivariable GEE analysis revealed that the stenosis severity (p = 0.004) and FAI at the maximum stenosis site of the ICA (p = 0.007) were capable of identifying symptomatic plaques. ROC analysis revealed that the FAI at the maximum stenosis site of the ICA, in combination with stenosis severity, resulted in a higher area under the curve (AUC) value (0.863) with moderate specificity (74%) and high sensitivity (89%).

Conclusion

The perivascular FAI at the maximum stenosis site of the ICA is useful for identifying symptomatic plaques by monitoring inflammation in patients with ICA atherosclerosis, which may provide a new inflammation marker for risk stratification of patients with stroke.