Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics

JACC-CARDIOVASCULAR IMAGING

卷:12

Article

Lee, Joo Myung^1,2  Choi, Gilwoo³  Koo, Bon-Kwon^4,5  Hwang, Doyeon⁴  Park, Jonghanne⁴  Zhang, Jinlong⁴  Kim, Kyung-Jin⁴  Tong, Yaliang⁶  Kim, Hyun Jin³  Grady, Leo³  Doh, Joon-Hyung⁷  Nam, Chang-Wook⁸  Shin, Eun-Seok⁹  Cho, Young-Seok¹⁰  Choi, Su-Yeon¹¹  Chun, Eun Ju¹²  Choi, Jin-Ho^1,2  Norgaard, Bjarne L.¹³  Christiansen, Evald H.¹³  Niemen, Koen^14,15  Otake, Hiromasa¹⁶  Penicka, Martin¹⁷  de Bruyne, Bernard¹⁷  Kubo, Takashi¹⁸  Akasaka, Takashi¹⁸  Narula, Jagat¹⁹  Douglas, Pamela S.²⁰  Taylor, Charles A.^3,21  Kim, Hyo-Soo⁴ 

[1] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Dept Internal Med, Seoul, South Korea

[2] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Cardiovasc Ctr, Seoul, South Korea

[3] HeartFlow Inc, Redwood City, CA USA

[4] Seoul Natl Univ Hosp, Dept Med, Seoul, South Korea

[5] Seoul Natl Univ, Inst Aging, Seoul, South Korea

[6] Jilin Univ, China Japan Union Hosp, Dept Cardiol, Changchun, Jilin, Peoples R China

[7] Inje Univ, Ilsan Paik Hosp, Dept Med, Goyang, South Korea

[8] Keimyung Univ, Dongsan Med Ctr, Dept Med, Daegu, South Korea

[9] Univ Ulsan, Coll Med, Ulsan Univ Hosp, Dept Cardiol, Ulsan, South Korea

[10] Seoul Natl Univ, Bundang Hosp, Dept Med, Seongnam, South Korea

[11] Seoul Natl Univ, Coll Med, Dept Internal Med, Healthcare Syst Gangnam Ctr, Seoul, South Korea

[12] Seoul Natl Univ, Bundang Hosp, Dept Radiol, Seongnam, South Korea

[13] Aarhus Univ Hosp, Dept Cardiol, Aarhus, Denmark

[14] Erasmus MC, Rotterdam, Netherlands

[15] Stanford Univ, Sch Med, Cardiovasc Inst, Stanford, CA 94305 USA

[16] Kobe Univ, Grad Sch Med, Dept Internal Med, Div Cardiovasc & Resp Med, Kobe, Hyogo, Japan

[17] OLV Clin, Cardiovasc Ctr Aalst, Aalst, Belgium

[18] Wakayama Med Univ, Dept Cardiovasc Med, Wakayama, Japan

[19] Icahn Sch Med Mt Sinai, New York, NY 10029 USA

[20] Duke Univ, Sch Med, Duke Clin Res Inst, Durham, NC USA

[21] Stanford Univ, Dept Bioengn, Stanford, CA 94305 USA

关键词: acute coronary syndrome;    adverse plaque characteristics;    axial plaque stress;    computational fluid dynamics;    coronary computed tomography angiography;    coronary plaque;    wall shear stress;   

DOI  :  10.1016/j.jcmg.2018.01.023

来源: Elsevier

【 摘 要 】

OBJECTIVES The authors investigated the utility of noninvasive hemodynamic assessment in the identification of high-risk plaques that caused subsequent acute coronary syndrome (ACS). BACKGROUND ACS is a critical event that impacts the prognosis of patients with coronary artery disease. However, the role of hemodynamic factors in the development of ACS is not well-known. METHODS Seventy-two patients with clearly documented ACS and available coronary computed tomographic angiography (CTA) acquired between 1 month and 2 years before the development of ACS were included. In 66 culprit and 150 nonculprit lesions as a case-control design, the presence of adverse plaque characteristics (APC) was assessed and hemodynamic parameters (fractional flow reserve derived by coronary computed tomographic angiography [FFRCT], change in FFRCT across the lesion [Delta FFRCT], wall shear stress [WSS], and axial plaque stress) were analyzed using computational fluid dynamics. The best cut-off values for FFRCT, Delta FFRCT, WSS, and axial plaque stress were used to define the presence of adverse hemodynamic characteristics (AHC). The incremental discriminant and reclassification abilities for ACS prediction were compared among 3 models (model 1: percent diameter stenosis [% DS] and lesion length, model 2: model 1 thorn APC, and model 3: model 2 thorn AHC). RESULTS The culprit lesions showed higher % DS (55.5 +/- 15.4% vs. 43.1 +/- 15.0%; p < 0.001) and higher prevalence of APC (80.3% vs. 42.0%; p < 0.001) than nonculprit lesions. Regarding hemodynamic parameters, culprit lesions showed lower FFRCT and higher Delta FFRCT, WSS, and axial plaque stress than nonculprit lesions (all p values < 0.01). Among the 3 models, model 3, which included hemodynamic parameters, showed the highest c-index, and better discrimination (concordance statistic [c-index] 0.789 vs. 0.747; p = 0.014) and reclassification abilities (category-free net reclassification index 0.287; p = 0.047; relative integrated discrimination improvement 0.368; p < 0.001) than model 2. Lesions with both APC and AHC showed significantly higher risk of the culprit for subsequent ACS than those with no APC/AHC (hazard ratio: 11.75; 95% confidence interval: 2.85 to 48.51; p +/- 0.001) and with either APC or AHC (hazard ratio: 3.22; 95% confidence interval: 1.86 to 5.55; p < 0.001). CONCLUSIONS Noninvasive hemodynamic assessment enhanced the identification of high-risk plaques that subsequently caused ACS. The integration of noninvasive hemodynamic assessments may improve the identification of culprit lesions for future ACS. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamic [EMERALD]; NCT02374775) (c) 2019 by the American College of Cardiology Foundation.

【 授权许可】

Free