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<p>Identifying high-risk plaques (HRPs) using non-invasive imaging modalities is clinically important. The diagnostic value of combining coronary computed tomography angiography (CCTA)–derived measurements with fractional flow reserve derived from computed tomography (FFR<sub>CT</sub>) for detecting HRPs in non-culprit lesions of acute coronary syndrome (ACS) remains to be clarified. This study aimed to assess whether ΔFFR<sub>CT</sub> and CCTA-derived plaque features can accurately identify HRPs detected by near-infrared spectroscopy and intravascular ultrasound (NIRS-IVUS) in non-culprit lesions of ACS. We prospectively evaluated 105 non-culprit coronary lesions using CCTA, FFR<sub>CT</sub>, and NIRS-IVUS in 32 patients with ACS. ΔFFR<sub>CT</sub> was calculated as the difference in FFR<sub>CT</sub> across the stenosis. Receiver operating characteristic (ROC) analysis determined the optimal cutoff values of ΔFFR<sub>CT</sub> and CCTA-derived plaque features for predicting a maximum 4-mm lipid core burden index (maxLCBI<sub>4mm</sub>) ≥ 400. Both ΔFFR<sub>CT</sub> values and CCTA-derived plaque features were associated with a maxLCBI<sub>4mm</sub> ≥ 400 (both <i>P</i> &lt; 0.05). The optimal cutoff values of ΔFFR<sub>CT</sub> and plaque density for predicting a maxLCBI<sub>4mm</sub> ≥ 400 were 0.06 and 29 Hounsfield units, respectively. The combination of ΔFFR<sub>CT</sub> ≥ 0.06 and low plaque density predicted a maxLCBI<sub>4mm</sub> ≥ 400 with 89.1% sensitivity and 84.8% specificity (area under the curve = 0.90; <i>P</i> &lt; 0.0001). In multivariate analysis, plaque density ≤ 29 HU and ΔFFR<sub>CT</sub> ≥ 0.06 independently predicted a maxLCBI<sub>4mm</sub>≥ 400. The combination of ΔFFR<sub>CT</sub> ≧0.06 and plaque density on CCTA predicted a maxLCBI<sub>4mm</sub> ≧400 with 89.1% sensitivity and 84.8% specificity (area under the curve, 0.90; <i>P</i> &lt; 0.0001). In multivariate analysis, plaque density ≦ 29 (odds ratio 7.72, 95% confidence interval 2.10–28.44, <i>P</i> = 0.002) and ΔFFR<sub>CT</sub> ≧0.06 (4.55, 1.21–17.04, <i>P</i> = 0.02) were independent predictors of a maxLCBI<sub>4mm</sub> ≧400. HRPs with a maxLCBI<sub>4mm</sub> ≧400 can be diagnosed with high accuracy by confirming a plaque density ≦ 29 in lesions with ΔFFR<sub>CT</sub> ≧0.06.</p>

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Non-invasive identification of high-risk plaques in non-culprit lesions of acute coronary syndrome

  • 期刊论文

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  • 发表日期：

    2026年2月16日

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  • Kazuyoshi Kakehi,
  • Masafumi Ueno,
  • Masaru Kayama,
  • Kei Hamanaka,
  • Haruka Minami,
  • Nobuhiro Yamada,
  • Kyohei Onishi,
  • Keishiro Sugimoto,
  • Yohei Funauchi,
  • Takayuki Kawamura,
  • Kosuke Fujita,
  • Koichiro Matsumura,
  • Gaku Nakazawa

摘要

Identifying high-risk plaques (HRPs) using non-invasive imaging modalities is clinically important. The diagnostic value of combining coronary computed tomography angiography (CCTA)–derived measurements with fractional flow reserve derived from computed tomography (FFRCT) for detecting HRPs in non-culprit lesions of acute coronary syndrome (ACS) remains to be clarified. This study aimed to assess whether ΔFFRCT and CCTA-derived plaque features can accurately identify HRPs detected by near-infrared spectroscopy and intravascular ultrasound (NIRS-IVUS) in non-culprit lesions of ACS. We prospectively evaluated 105 non-culprit coronary lesions using CCTA, FFRCT, and NIRS-IVUS in 32 patients with ACS. ΔFFRCT was calculated as the difference in FFRCT across the stenosis. Receiver operating characteristic (ROC) analysis determined the optimal cutoff values of ΔFFRCT and CCTA-derived plaque features for predicting a maximum 4-mm lipid core burden index (maxLCBI4mm) ≥ 400. Both ΔFFRCT values and CCTA-derived plaque features were associated with a maxLCBI4mm ≥ 400 (both P < 0.05). The optimal cutoff values of ΔFFRCT and plaque density for predicting a maxLCBI4mm ≥ 400 were 0.06 and 29 Hounsfield units, respectively. The combination of ΔFFRCT ≥ 0.06 and low plaque density predicted a maxLCBI4mm ≥ 400 with 89.1% sensitivity and 84.8% specificity (area under the curve = 0.90; P < 0.0001). In multivariate analysis, plaque density ≤ 29 HU and ΔFFRCT ≥ 0.06 independently predicted a maxLCBI4mm≥ 400. The combination of ΔFFRCT ≧0.06 and plaque density on CCTA predicted a maxLCBI4mm ≧400 with 89.1% sensitivity and 84.8% specificity (area under the curve, 0.90; P < 0.0001). In multivariate analysis, plaque density ≦ 29 (odds ratio 7.72, 95% confidence interval 2.10–28.44, P = 0.002) and ΔFFRCT ≧0.06 (4.55, 1.21–17.04, P = 0.02) were independent predictors of a maxLCBI4mm ≧400. HRPs with a maxLCBI4mm ≧400 can be diagnosed with high accuracy by confirming a plaque density ≦ 29 in lesions with ΔFFRCT ≧0.06.