Objectives To evaluate carotid computed tomography angiography (CTA) performance in assessing MRI-defined plaque vulnerability using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) as the reference, and to develop a multidimensional predictive model integrating plaque composition, geometry, and perivascular adipose tissue (PVAT). Materials and methods Patients undergoing both CTA and HR-MR-VWI were retrospectively included. Plaques were classified by modified AHA criteria and co-registered to ensure spatial correspondence. Quantitative CTA features were extracted via semi-automated segmentation. A historical cohort (2018–2024) was partitioned into training (n = 130) and internal validation (n = 57) sets; a recent cohort (2024–2025) served as a prospective temporal test set (n = 78). A multivariate logistic regression model was developed and evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results In 265 plaques, PVAT attenuation (OR = 1.05; p < 0.001) and maximum diameter stenosis (MDS) (OR = 1.03; p < 0.05) emerged as independent predictors of MRI-defined vulnerability. The combined model achieved robust discrimination with AUCs of 0.86, 0.80, and 0.85 in the training, internal validation, and prospective temporal test sets, respectively. Calibration and decision curve analysis demonstrated excellent agreement and clinical net benefit across all cohorts. Conclusion CTA-derived MDS and PVAT attenuation are robust independent predictors of MRI-defined carotid plaque vulnerability. This supportive, proof-of-concept nomogram offers a tool for characterizing high-risk plaque phenotypes, highlighting CTA as a viable supplementary tool to MRI in routine practice. Key Points <Emphasis Type="BoldItalic">Question</Emphasis> Can a multidimensional carotid CTA model, integrating perivascular adipose tissue and luminal geometry, accurately identify high-risk plaque phenotypes compared to high-resolution MRI? <Emphasis Type="BoldItalic">Findings</Emphasis> CTA-derived perivascular fat attenuation and stenosis severity are independent predictors of MRI-defined plaque vulnerability, achieving robust diagnostic performance across internal and temporal validation. <Emphasis Type="BoldItalic">Clinical relevance</Emphasis> This plaque-level CTA model provides a rapid, accessible tool for identifying MRI-defined vulnerable carotid plaques and personalized management in routine clinical practice where MRI access is limited. Graphical Abstract

Plaque-level comparison of carotid CTA and high-resolution magnetic resonance vessel wall imaging for assessing MRI-defined plaque vulnerability

期刊论文
发表日期：

2026年3月28日

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Juan Long,
Xiaohan Liu,
He Zhang,
Zhen Wang,
He Zhang,
Zhongxiao Liu,
Aiyun Sun,
Yankai Meng,
Kai Xu

摘要

Objectives

To evaluate carotid computed tomography angiography (CTA) performance in assessing MRI-defined plaque vulnerability using high-resolution magnetic resonance vessel wall imaging (HR-MR-VWI) as the reference, and to develop a multidimensional predictive model integrating plaque composition, geometry, and perivascular adipose tissue (PVAT).

Materials and methods

Patients undergoing both CTA and HR-MR-VWI were retrospectively included. Plaques were classified by modified AHA criteria and co-registered to ensure spatial correspondence. Quantitative CTA features were extracted via semi-automated segmentation. A historical cohort (2018–2024) was partitioned into training (n = 130) and internal validation (n = 57) sets; a recent cohort (2024–2025) served as a prospective temporal test set (n = 78). A multivariate logistic regression model was developed and evaluated using the area under the receiver operating characteristic curve (AUC) and decision curve analysis.

Results

In 265 plaques, PVAT attenuation (OR = 1.05; p < 0.001) and maximum diameter stenosis (MDS) (OR = 1.03; p < 0.05) emerged as independent predictors of MRI-defined vulnerability. The combined model achieved robust discrimination with AUCs of 0.86, 0.80, and 0.85 in the training, internal validation, and prospective temporal test sets, respectively. Calibration and decision curve analysis demonstrated excellent agreement and clinical net benefit across all cohorts.

Conclusion

CTA-derived MDS and PVAT attenuation are robust independent predictors of MRI-defined carotid plaque vulnerability. This supportive, proof-of-concept nomogram offers a tool for characterizing high-risk plaque phenotypes, highlighting CTA as a viable supplementary tool to MRI in routine practice.

Key Points

Question Can a multidimensional carotid CTA model, integrating perivascular adipose tissue and luminal geometry, accurately identify high-risk plaque phenotypes compared to high-resolution MRI?

Findings CTA-derived perivascular fat attenuation and stenosis severity are independent predictors of MRI-defined plaque vulnerability, achieving robust diagnostic performance across internal and temporal validation.

Clinical relevance This plaque-level CTA model provides a rapid, accessible tool for identifying MRI-defined vulnerable carotid plaques and personalized management in routine clinical practice where MRI access is limited.

Graphical Abstract