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Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics.
JACC Cardiovasc Imaging. 2019 06; 12(6):1032-1043.JC

Abstract

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 [△FFRCT], wall shear stress [WSS], and axial plaque stress) were analyzed using computational fluid dynamics. The best cut-off values for FFRCT, △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 + APC, and model 3: model 2 + 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 △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).

Authors+Show Affiliations

Department of Internal Medicine and Cardiovascular Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.HeartFlow, Inc., Redwood City, California.Department of Medicine, Seoul National University Hospital, Seoul, South Korea; Institute on Aging, Seoul National University, Seoul, Korea. Electronic address: bkkoo@snu.ac.kr.Department of Medicine, Seoul National University Hospital, Seoul, South Korea.Department of Medicine, Seoul National University Hospital, Seoul, South Korea.Department of Medicine, Seoul National University Hospital, Seoul, South Korea.Department of Medicine, Seoul National University Hospital, Seoul, South Korea.Department of Cardiology, China-Japan Union Hospital of Jilin University, Changchun, China.HeartFlow, Inc., Redwood City, California.HeartFlow, Inc., Redwood City, California.Department of Medicine, Inje University Ilsan Paik Hospital, Goyang, South Korea.Department of Medicine, Keimyung University Dongsan Medical Center, Daegu, South Korea.Department of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, South Korea.Department of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea.Department of Internal Medicine, Seoul National University Healthcare System Gangnam Center, Seoul National University College of Medicine, Seoul, South Korea.Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea.Department of Internal Medicine and Cardiovascular Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.Erasmus University Medical Center, Rotterdam, the Netherlands; Cardiovascular Institute, Stanford University, School of Medicine, Stanford, California.Department of Internal Medicine, Division of Cardiovascular and Respiratory Medicine, Kobe University Graduate School of Medicine, Kobe, Japan.Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium.Cardiovascular Center Aalst, OLV-Clinic, Aalst, Belgium.Department of Cardiovascular Medicine, Wakayama Medical University, Wakayama, Japan.Department of Cardiovascular Medicine, Wakayama Medical University, Wakayama, Japan.Icahn School of Medicine at Mount Sinai Hospital, New York, New York.Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.HeartFlow, Inc., Redwood City, California; Department of Bioengineering, Stanford University, Stanford, California.Department of Medicine, Seoul National University Hospital, Seoul, South Korea.

Pub Type(s)

Comparative Study
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

29550316

Citation

Lee, Joo Myung, et al. "Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics." JACC. Cardiovascular Imaging, vol. 12, no. 6, 2019, pp. 1032-1043.
Lee JM, Choi G, Koo BK, et al. Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. JACC Cardiovasc Imaging. 2019;12(6):1032-1043.
Lee, J. M., Choi, G., Koo, B. K., Hwang, D., Park, J., Zhang, J., Kim, K. J., Tong, Y., Kim, H. J., Grady, L., Doh, J. H., Nam, C. W., Shin, E. S., Cho, Y. S., Choi, S. Y., Chun, E. J., Choi, J. H., Nørgaard, B. L., Christiansen, E. H., ... Kim, H. S. (2019). Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. JACC. Cardiovascular Imaging, 12(6), 1032-1043. https://doi.org/10.1016/j.jcmg.2018.01.023
Lee JM, et al. Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. JACC Cardiovasc Imaging. 2019;12(6):1032-1043. PubMed PMID: 29550316.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. AU - Lee,Joo Myung, AU - Choi,Gilwoo, AU - Koo,Bon-Kwon, AU - Hwang,Doyeon, AU - Park,Jonghanne, AU - Zhang,Jinlong, AU - Kim,Kyung-Jin, AU - Tong,Yaliang, AU - Kim,Hyun Jin, AU - Grady,Leo, AU - Doh,Joon-Hyung, AU - Nam,Chang-Wook, AU - Shin,Eun-Seok, AU - Cho,Young-Seok, AU - Choi,Su-Yeon, AU - Chun,Eun Ju, AU - Choi,Jin-Ho, AU - Nørgaard,Bjarne L, AU - Christiansen,Evald H, AU - Niemen,Koen, AU - Otake,Hiromasa, AU - Penicka,Martin, AU - de Bruyne,Bernard, AU - Kubo,Takashi, AU - Akasaka,Takashi, AU - Narula,Jagat, AU - Douglas,Pamela S, AU - Taylor,Charles A, AU - Kim,Hyo-Soo, Y1 - 2018/03/14/ PY - 2017/10/15/received PY - 2018/01/08/revised PY - 2018/01/09/accepted PY - 2018/3/20/pubmed PY - 2020/3/19/medline PY - 2018/3/19/entrez KW - acute coronary syndrome KW - adverse plaque characteristics KW - axial plaque stress KW - computational fluid dynamics KW - coronary computed tomography angiography KW - coronary plaque KW - wall shear stress SP - 1032 EP - 1043 JF - JACC. Cardiovascular imaging JO - JACC Cardiovasc Imaging VL - 12 IS - 6 N2 - 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 [△FFRCT], wall shear stress [WSS], and axial plaque stress) were analyzed using computational fluid dynamics. The best cut-off values for FFRCT, △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 + APC, and model 3: model 2 + 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 △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). SN - 1876-7591 UR - https://www.unboundmedicine.com/medline/citation/29550316/Identification_of_High_Risk_Plaques_Destined_to_Cause_Acute_Coronary_Syndrome_Using_Coronary_Computed_Tomographic_Angiography_and_Computational_Fluid_Dynamics_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1936-878X(18)30134-7 DB - PRIME DP - Unbound Medicine ER -