Risk Stratification in Acute Coronary Syndrome by Comprehensive Morphofunctional Assessment With Optical Coherence Tomography

Huihong Hong; Haibo Jia; Ming Zeng; Juan Luis Gutiérrez-Chico; Yini Wang; Xiaoling Zeng; Yuhan Qin; Chen Zhao; Miao Chu; Jiayue Huang; Lili Liu; Sining Hu; Luping He; Lianglong Chen; William Wijns; Bo Yu; Shengxian Tu

doi:10.1016/j.jacasi.2022.03.004

Risk Stratification in Acute Coronary Syndrome by Comprehensive Morphofunctional Assessment With Optical Coherence Tomography

JACC Asia. 2022 May 24;2(4):460-472. doi: 10.1016/j.jacasi.2022.03.004. eCollection 2022 Aug.

Authors

Huihong Hong^{1

2}, Haibo Jia³, Ming Zeng³, Juan Luis Gutiérrez-Chico⁴, Yini Wang³, Xiaoling Zeng², Yuhan Qin³, Chen Zhao³, Miao Chu¹, Jiayue Huang⁵, Lili Liu⁴, Sining Hu³, Luping He³, Lianglong Chen², William Wijns⁵, Bo Yu³, Shengxian Tu^{1

2}

Affiliations

¹ Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
² Department of Cardiology, Fujian Medical University Union Hospital, Fuzhou, China.
³ Department of Cardiology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China.
⁴ Department of Cardiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁵ The Lambe Institute for Translational Medicine and Curam, National University of Ireland Galway, Galway, Ireland.

Abstract

Background: Artificial intelligence enables simultaneous evaluation of plaque morphology and computational physiology from optical coherence tomography (OCT).

Objectives: This study sought to appraise the predictive value of major adverse cardiovascular events (MACE) by combined plaque morphology and computational physiology.

Methods: A total of 604 patients with acute coronary syndrome who underwent OCT imaging in ≥1 nonculprit vessel during index coronary angiography were retrospectively enrolled. A novel morphologic index, named the lipid-to-cap ratio (LCR), and a functional parameter to evaluate the physiologic significance of coronary stenosis from OCT, namely, the optical flow ratio (OFR), were calculated from OCT, together with classical morphologic parameters, like thin-cap fibroatheroma (TCFA) and minimal lumen area.

Results: The 2-year cumulative incidence of a composite of nonculprit vessel-related cardiac death, cardiac arrest, acute myocardial infarction, and ischemia-driven revascularization (NCV-MACE) at 2 years was 4.3%. Both LCR (area under the curve [AUC]: 0.826; 95% CI: 0.793-0.855) and OFR (AUC: 0.838; 95% CI: 0.806-0.866) were superior to minimal lumen area (AUC: 0.618; 95% CI: 0.578-0.657) in predicting NCV-MACE at 2 years. Patients with both an LCR of >0.33 and an OFR of ≤0.84 had significantly higher risk of NCV-MACE at 2 years than patients in whom at least 1 of these 2 parameters was normal (HR: 42.73; 95% CI: 12.80-142.60; P < 0.001). The combination of thin-cap fibroatheroma and OFR also identified patients at higher risk of future events (HR: 6.58; 95% CI: 2.83-15.33; P < 0.001).

Conclusions: The combination of LCR with OFR permits the identification of a subgroup of patients with 43-fold higher risk of recurrent cardiovascular events in the nonculprit vessels after acute coronary syndrome.

Keywords: ACS, acute coronary syndrome; AI, artificial intelligence; AUC, area under the curve; FCT, fibrous cap thickness; FFR, fractional flow reserve; LAD, left anterior descending; LCR, lipid-to-cap ratio; MACE, major adverse cardiovascular events; MI, myocardial infarction; MLA, minimal lumen area; NCV-MACE, nonculprit vessel–related major adverse cardiovascular events; OCT, optical coherence tomography; OFR, optical flow ratio; PCI, percutaneous coronary intervention; ROC, receiver-operating characteristic; TCFA, thin-cap fibroatheroma; acute coronary syndrome; coronary physiology; iFR, instantaneous wave-free ratio; optical coherence tomography; optical flow ratio; thin-cap fibroatheroma; vulnerable plaque.