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

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.

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Journal
Heart and Vessels
Published
2026-02-16
DOI
https://doi.org/10.1007/s00380-026-02663-6
Primary Topic
Coronary Interventions and Diagnostics
Type
article
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article

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

Keishiro Sugimoto, Haruka Minami, Yohei Funauchi, Koichiro Matsumura et al.
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Non-invasive identification of high-risk plaques in non-culprit lesions of acute coronary syndrome

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

Abstract

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.

Heart and Vessels
Kindai University (JP)
Good health and well-being
Openalex Percentile: Top 54%
Coronary Interventions and Diagnostics
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