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Background <p>Perivascular adipose tissue (PCAT) inflammation contributes to plaque vulnerability in coronary artery atherosclerotic heart disease (CHD). The fat attenuation index (FAI) has emerged as a non-invasive marker of vascular inflammation. However, its association with plaque characteristics, particularly high-risk plaques (HRPs), remains insufficiently understood. This study evaluated coronary peri-vascular FAI using dual-layer spectral CT (SDCT) and its relationship with plaque calcification and HRP identification.</p> Methods <p>A retrospective analysis of 182 patients with CHD and 312 plaques was conducted. FAI was measured on 120 kVp images, virtual monoenergetic images, and effective atomic number (Eff-Z) images across energy levels from 40&#xa0;keV to 100&#xa0;keV. The spectral slope (λ<sub>HU</sub>) was also calculated. The relationship between FAI and plaque calcification was assessed, and differences in quantitative parameters between high-risk and non-high-risk plaque groups were used to determine optimal cut-off values for differentiating HRPs.</p> Results <p>As plaque calcification increased, FAI values generally decreased. The fat attenuation values around HRPs were significantly higher than those around non-HRPs. Additionally, λ<sub>Hu</sub> (λ<sub>40-70 keV</sub>, λ<sub>40-100 keV</sub>) and Eff-Z values were significantly higher in HRPs compared to non-HRPs (all <i>p</i> &lt; 0.001). Multivariate logistic regression identified FAI at 40&#xa0;keV, λ<sub>40-70 keV</sub>, and Eff-Z as independent predictors for HRP diagnosis. The combined model of these parameters had the highest diagnostic efficacy, with an AUC of 0.881, sensitivity of 87.1%, and specificity of 75.0%.</p> Conclusion <p>FAI assessed using SDCT demonstrates enhanced discrimination of plaque composition and characteristics compared to conventional CT. The combined model of FAI40keV, λ40–70&#xa0;keV, and Eff-Z shows the highest discriminative ability for high-risk plaque features, suggesting potential value for non-invasive plaque characterization that warrants prospective validation.</p>

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Quantitative assessment of coronary peri-vascular fat attenuation index using dual-layer spectral CT for differentiating high-risk plaques in coronary artery disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月30日

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  • Yipei Song,
  • Ao Kan,
  • Mengyao Hu,
  • Ying Liu,
  • Ziyan Feng,
  • Qimin Fang,
  • Xiwen Wang,
  • Mengni Jin,
  • Lianggeng Gong

摘要

Background

Perivascular adipose tissue (PCAT) inflammation contributes to plaque vulnerability in coronary artery atherosclerotic heart disease (CHD). The fat attenuation index (FAI) has emerged as a non-invasive marker of vascular inflammation. However, its association with plaque characteristics, particularly high-risk plaques (HRPs), remains insufficiently understood. This study evaluated coronary peri-vascular FAI using dual-layer spectral CT (SDCT) and its relationship with plaque calcification and HRP identification.

Methods

A retrospective analysis of 182 patients with CHD and 312 plaques was conducted. FAI was measured on 120 kVp images, virtual monoenergetic images, and effective atomic number (Eff-Z) images across energy levels from 40 keV to 100 keV. The spectral slope (λHU) was also calculated. The relationship between FAI and plaque calcification was assessed, and differences in quantitative parameters between high-risk and non-high-risk plaque groups were used to determine optimal cut-off values for differentiating HRPs.

Results

As plaque calcification increased, FAI values generally decreased. The fat attenuation values around HRPs were significantly higher than those around non-HRPs. Additionally, λHu (λ40-70 keV, λ40-100 keV) and Eff-Z values were significantly higher in HRPs compared to non-HRPs (all p < 0.001). Multivariate logistic regression identified FAI at 40 keV, λ40-70 keV, and Eff-Z as independent predictors for HRP diagnosis. The combined model of these parameters had the highest diagnostic efficacy, with an AUC of 0.881, sensitivity of 87.1%, and specificity of 75.0%.

Conclusion

FAI assessed using SDCT demonstrates enhanced discrimination of plaque composition and characteristics compared to conventional CT. The combined model of FAI40keV, λ40–70 keV, and Eff-Z shows the highest discriminative ability for high-risk plaque features, suggesting potential value for non-invasive plaque characterization that warrants prospective validation.