Objectives <p>This study aimed to investigate the relationship between perivascular fat density (PFD) and carotid plaque characteristics while exploring the additive diagnostic value of PFD in predicting symptomatic carotid plaques.</p> Materials and Methods <p>In a single-center retrospective case-control study, 315 patients with unilateral carotid atherosclerosis were classified into symptomatic and asymptomatic groups based on the presence of acute ischemic stroke or transient ischemic attack (TIA) within 2 weeks before carotid computed tomography angiography (CTA). Plaque CTA features and PFD were assessed, and their relationship was analyzed using Spearman’s rank correlation. Logistic regression analysis was employed to identify risk factors for symptomatic carotid plaques, and predictive models were subsequently developed. The performance of these models was further evaluated.</p> Results <p>A positive linear correlation was found between PFD and plaque CTA characteristics (<i>p</i> &lt; 0.05). PFD, degree of stenosis, plaque burden, and soft plaque thickness were identified as predictors of symptomatic carotid plaques. Receiver operating characteristic (ROC) curves showed that the areas under the curves (AUC) increased from 0.631 to 0.846 with the addition of plaque burden, soft plaque thickness, and PFD to a degree of stenosis. The calibration curves of the combined model with PFD and plaque risk features demonstrated good predictive consistency. Decision curve analysis suggested that the combined model provided higher clinical benefit.</p> Conclusions <p>PFD may serve as a valuable imaging marker for vulnerable plaques, providing additional diagnostic value in risk assessment. The combination of PFD with plaque risk features may further enhance the predictive performance of symptomatic carotid plaques.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>Does perivascular fat density (PFD) add additional predictive value to plaque risk features on CT angiography (CTA) in the assessment of symptomatic carotid plaques?</i></p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>PFD provides additive predictive value for symptomatic carotid plaques. Combining PFD with stenosis severity and plaque CTA features improves prediction</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>PFD may serve as a valuable imaging biomarker for risk stratification and clinical decision-making in carotid atherosclerosis</i>.</p> Graphical Abstract <p></p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Additive value of perivascular fat density to CT angiography characteristics of carotid plaques in predicting symptomatic carotid plaques

  • Wei Luo,
  • Peng Lv,
  • Ranying Zhang,
  • Qixuan Qiu,
  • Jiang Lin

摘要

Objectives

This study aimed to investigate the relationship between perivascular fat density (PFD) and carotid plaque characteristics while exploring the additive diagnostic value of PFD in predicting symptomatic carotid plaques.

Materials and Methods

In a single-center retrospective case-control study, 315 patients with unilateral carotid atherosclerosis were classified into symptomatic and asymptomatic groups based on the presence of acute ischemic stroke or transient ischemic attack (TIA) within 2 weeks before carotid computed tomography angiography (CTA). Plaque CTA features and PFD were assessed, and their relationship was analyzed using Spearman’s rank correlation. Logistic regression analysis was employed to identify risk factors for symptomatic carotid plaques, and predictive models were subsequently developed. The performance of these models was further evaluated.

Results

A positive linear correlation was found between PFD and plaque CTA characteristics (p < 0.05). PFD, degree of stenosis, plaque burden, and soft plaque thickness were identified as predictors of symptomatic carotid plaques. Receiver operating characteristic (ROC) curves showed that the areas under the curves (AUC) increased from 0.631 to 0.846 with the addition of plaque burden, soft plaque thickness, and PFD to a degree of stenosis. The calibration curves of the combined model with PFD and plaque risk features demonstrated good predictive consistency. Decision curve analysis suggested that the combined model provided higher clinical benefit.

Conclusions

PFD may serve as a valuable imaging marker for vulnerable plaques, providing additional diagnostic value in risk assessment. The combination of PFD with plaque risk features may further enhance the predictive performance of symptomatic carotid plaques.

Key Points

Question Does perivascular fat density (PFD) add additional predictive value to plaque risk features on CT angiography (CTA) in the assessment of symptomatic carotid plaques?

Findings PFD provides additive predictive value for symptomatic carotid plaques. Combining PFD with stenosis severity and plaque CTA features improves prediction.

Clinical relevance PFD may serve as a valuable imaging biomarker for risk stratification and clinical decision-making in carotid atherosclerosis.

Graphical Abstract