Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II (EMERALD II) Study

NCT ID: NCT03591328

Last Updated: 2022-08-23

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

UNKNOWN

Total Enrollment

429 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-07-09

Study Completion Date

2022-12-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The EMERALD II study is a multinational, multicenter, and retrospective study. ACS patients who underwent CCTA from 1 months to 3 years prior to the event will be retrospectively identified. Plaques in the non-culprit vessels will be regarded as a primary control group.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

The mechanisms of plaque rupture are not fully understood. Hemodynamic forces, plaque vulnerability, and the interaction between these factors may cause plaque instability and subsequent acute coronary syndrome (ACS). Previously, the first-in-human study, EMERALD I, showed that the addition of hemodynamic parameters calculated noninvasively from coronary computed tomography (CCTA) using computational fluid dynamics (CFD) improved the ability to predict the risk of ACS compared with conventional approaches based on anatomical stenosis severity and adverse plaque characteristics. In addition to hemodynamic properties, quantified compositional plaque volumes such as fibrofatty and necrotic core volume (FFNC) or low-attenuation plaque burden (% plaque to vessel volume) have been proven to be robust prognostic indicators of ACS. While various hemodynamic and plaque features predictive of ACS have been introduced, the relative importance among them and the additive value of the risk model with the best features over the current diagnostic scheme of CCTA have not been proposed. In this regard, we designed the subsequent EMERALD II study to find the best hemodynamic and plaque features in prediction of ACS from comprehensive CCTA analysis, including per-lesion and per-vessel plaque quantification and hemodynamic analysis, and to investigate whether a comprehensive risk prediction model with them has an incremental value in a larger population.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Acute Myocardial Infarction Unstable Angina

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Observational Model Type

CASE_CONTROL

Study Time Perspective

OTHER

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Culprit

Plaques which is related with acute coronary syndrome

Coronary CT angiography

Intervention Type DIAGNOSTIC_TEST

Comprehensive CCTA analysis of all culprit and non-culprit lesions to obtain their per-lesion and per-vessel quantitative, qualitative plaque, and hemodynamic features is performed by the independent core laboratory (HeartFlow, Mountain View, CA, USA) blinded to patient characteristics and ICA findings.

The current CCTA reporting variables, including % diameter stenosis, segment involvement score (SIS), and HRP features, are obtained for all lesions by another independent core laboratory (University of British Columbia, Vancouver, Canada) to construct a reference model. ICA and invasive imaging studies performed at the event of ACS are analyzed by the independent core laboratory (Samsung Medical Center, Seoul, Korea) to define the culprit lesion blinded to CCTA findings. Other independent experts match culprit and non-culprit lesion data between ICA and CCTA findings.

Non-culprit

Plaques which is not related with acute coronary syndrome

Coronary CT angiography

Intervention Type DIAGNOSTIC_TEST

Comprehensive CCTA analysis of all culprit and non-culprit lesions to obtain their per-lesion and per-vessel quantitative, qualitative plaque, and hemodynamic features is performed by the independent core laboratory (HeartFlow, Mountain View, CA, USA) blinded to patient characteristics and ICA findings.

The current CCTA reporting variables, including % diameter stenosis, segment involvement score (SIS), and HRP features, are obtained for all lesions by another independent core laboratory (University of British Columbia, Vancouver, Canada) to construct a reference model. ICA and invasive imaging studies performed at the event of ACS are analyzed by the independent core laboratory (Samsung Medical Center, Seoul, Korea) to define the culprit lesion blinded to CCTA findings. Other independent experts match culprit and non-culprit lesion data between ICA and CCTA findings.

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Coronary CT angiography

Comprehensive CCTA analysis of all culprit and non-culprit lesions to obtain their per-lesion and per-vessel quantitative, qualitative plaque, and hemodynamic features is performed by the independent core laboratory (HeartFlow, Mountain View, CA, USA) blinded to patient characteristics and ICA findings.

The current CCTA reporting variables, including % diameter stenosis, segment involvement score (SIS), and HRP features, are obtained for all lesions by another independent core laboratory (University of British Columbia, Vancouver, Canada) to construct a reference model. ICA and invasive imaging studies performed at the event of ACS are analyzed by the independent core laboratory (Samsung Medical Center, Seoul, Korea) to define the culprit lesion blinded to CCTA findings. Other independent experts match culprit and non-culprit lesion data between ICA and CCTA findings.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. Patients who presented with ACS\* and underwent invasive coronary angiography with identifiable culprit lesion
2. The patients who underwent coronary CT angiography, regardless of the reason (for example, routine healthcare check-up, or evaluation for stable angina or atypical chest pain) prior to the acute event.
3. Time limit of CCTA: 1 months \~ 3 years prior to the event.

* Definition of ACS:

A. The patients with acute myocardial infarction should have cardiac enzyme elevation and identified culprit lesion confirmed by invasive coronary angiography, IVUS, or OCT.

B. The patients with unstable angina should have evidence of plaque rupture, which includes at least one of the following: (1) the presence of plaque rupture or haziness including thrombus at invasive coronary angiography, (2) angiographic stenosis ≥90%, or (3) the evidence of rupture confirmed by IVUS or OCT.

Exclusion Criteria

1. Patients with ACS without clear evidence of culprit lesion
2. Patients with stents in two or more vessel territories prior to CCTA
3. Poor quality of CCTA which is unsuitable for plaque and CFD analysis
4. Patients with ACS culprit lesion in a stented segment
5. Patients with previous history of coronary artery bypass graft surgery
6. Patients with revascularization after CCTA and before ACS event (\*Patients with elective PCI for 1 vessel within 3 month after CCTA can be enrolled.
7. Secondary ACS due to other general medical conditions, such as sepsis, arrhythmia, bleeding, etc.
9. Poor quality CCTA images unsuitable for CFD and plaque analysis
10. No unprocessed CCTA data
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Inje University Ilsan Paik Hospital

OTHER

Sponsor Role collaborator

St. Mary's hostpital

UNKNOWN

Sponsor Role collaborator

Odense University Hospital

OTHER

Sponsor Role collaborator

University of Milan

OTHER

Sponsor Role collaborator

Imperial College London

OTHER

Sponsor Role collaborator

Aarhus University Hospital

OTHER

Sponsor Role collaborator

Semmelweis University

OTHER

Sponsor Role collaborator

Oxford University Hospitals NHS Trust

OTHER

Sponsor Role collaborator

Emory University

OTHER

Sponsor Role collaborator

Ehime University Graduate School of Medicine

OTHER

Sponsor Role collaborator

Gifu Heart Center

OTHER

Sponsor Role collaborator

Wakayama Medical University

OTHER

Sponsor Role collaborator

Keimyung University Dongsan Medical Center

OTHER

Sponsor Role collaborator

Seoul National University Bundang Hospital

OTHER

Sponsor Role collaborator

Seoul National University Hospital Healthcare System Gangnam Center

UNKNOWN

Sponsor Role collaborator

Chosun University Hospital

OTHER

Sponsor Role collaborator

Chungnam National University Hospital

OTHER

Sponsor Role collaborator

Monzino Cardiology Center

UNKNOWN

Sponsor Role collaborator

OLV Hospital

UNKNOWN

Sponsor Role collaborator

Monash Heart

UNKNOWN

Sponsor Role collaborator

University of British Columbia

OTHER

Sponsor Role collaborator

MOUNT SINAI HOSPITAL

OTHER

Sponsor Role collaborator

Tokyo Medical University Hachioji Medical Center

UNKNOWN

Sponsor Role collaborator

Tokai University

OTHER

Sponsor Role collaborator

St. Luke's International Hospital

UNKNOWN

Sponsor Role collaborator

Aichi Medical University

OTHER

Sponsor Role collaborator

Toyohashi Heart Center

OTHER

Sponsor Role collaborator

Kobe University Hospital

UNKNOWN

Sponsor Role collaborator

National Cerebral and Cardiovascular Center, Japan

OTHER

Sponsor Role collaborator

Shin Koga Hospital

UNKNOWN

Sponsor Role collaborator

Saiseikai Kumamoto Hospital

UNKNOWN

Sponsor Role collaborator

Tsuchiura Kyodo Hospital

UNKNOWN

Sponsor Role collaborator

Tokyo Medical Dental University

UNKNOWN

Sponsor Role collaborator

Loyola University

OTHER

Sponsor Role collaborator

Leiden University

OTHER

Sponsor Role collaborator

Weil Cornell Medical College

UNKNOWN

Sponsor Role collaborator

West Penn Allegheny Health System

OTHER

Sponsor Role collaborator

Ulsan Hospital

UNKNOWN

Sponsor Role collaborator

Ulsan University Hospital

OTHER

Sponsor Role collaborator

Seoul National University Hospital

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Bon-Kwon Koo

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Bon-Kwon Koo, MD,PhD

Role: STUDY_CHAIR

Seoul National University Hospital

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Seoul National University Hospital

Seoul, , South Korea

Site Status

Countries

Review the countries where the study has at least one active or historical site.

South Korea

References

Explore related publications, articles, or registry entries linked to this study.

Koskinas KC, Ughi GJ, Windecker S, Tearney GJ, Raber L. Intracoronary imaging of coronary atherosclerosis: validation for diagnosis, prognosis and treatment. Eur Heart J. 2016 Feb 7;37(6):524-35a-c. doi: 10.1093/eurheartj/ehv642. Epub 2015 Dec 11.

Reference Type BACKGROUND
PMID: 26655874 (View on PubMed)

Stone GW, Maehara A, Lansky AJ, de Bruyne B, Cristea E, Mintz GS, Mehran R, McPherson J, Farhat N, Marso SP, Parise H, Templin B, White R, Zhang Z, Serruys PW; PROSPECT Investigators. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011 Jan 20;364(3):226-35. doi: 10.1056/NEJMoa1002358.

Reference Type BACKGROUND
PMID: 21247313 (View on PubMed)

Prati F, Romagnoli E, Gatto L, La Manna A, Burzotta F, Ozaki Y, Marco V, Boi A, Fineschi M, Fabbiocchi F, Taglieri N, Niccoli G, Trani C, Versaci F, Calligaris G, Ruscica G, Di Giorgio A, Vergallo R, Albertucci M, Biondi-Zoccai G, Tamburino C, Crea F, Alfonso F, Arbustini E. Relationship between coronary plaque morphology of the left anterior descending artery and 12 months clinical outcome: the CLIMA study. Eur Heart J. 2020 Jan 14;41(3):383-391. doi: 10.1093/eurheartj/ehz520.

Reference Type BACKGROUND
PMID: 31504405 (View on PubMed)

Maurovich-Horvat P, Ferencik M, Voros S, Merkely B, Hoffmann U. Comprehensive plaque assessment by coronary CT angiography. Nat Rev Cardiol. 2014 Jul;11(7):390-402. doi: 10.1038/nrcardio.2014.60. Epub 2014 Apr 22.

Reference Type BACKGROUND
PMID: 24755916 (View on PubMed)

Motoyama S, Ito H, Sarai M, Kondo T, Kawai H, Nagahara Y, Harigaya H, Kan S, Anno H, Takahashi H, Naruse H, Ishii J, Hecht H, Shaw LJ, Ozaki Y, Narula J. Plaque Characterization by Coronary Computed Tomography Angiography and the Likelihood of Acute Coronary Events in Mid-Term Follow-Up. J Am Coll Cardiol. 2015 Jul 28;66(4):337-46. doi: 10.1016/j.jacc.2015.05.069.

Reference Type BACKGROUND
PMID: 26205589 (View on PubMed)

Yang S, Koo BK, Narula J. Interactions Between Morphological Plaque Characteristics and Coronary Physiology: From Pathophysiological Basis to Clinical Implications. JACC Cardiovasc Imaging. 2022 Jun;15(6):1139-1151. doi: 10.1016/j.jcmg.2021.10.009. Epub 2021 Dec 15.

Reference Type BACKGROUND
PMID: 34922863 (View on PubMed)

Taylor CA, Fonte TA, Min JK. Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol. 2013 Jun 4;61(22):2233-41. doi: 10.1016/j.jacc.2012.11.083. Epub 2013 Apr 3.

Reference Type BACKGROUND
PMID: 23562923 (View on PubMed)

Choi G, Lee JM, Kim HJ, Park JB, Sankaran S, Otake H, Doh JH, Nam CW, Shin ES, Taylor CA, Koo BK. Coronary Artery Axial Plaque Stress and its Relationship With Lesion Geometry: Application of Computational Fluid Dynamics to Coronary CT Angiography. JACC Cardiovasc Imaging. 2015 Oct;8(10):1156-1166. doi: 10.1016/j.jcmg.2015.04.024. Epub 2015 Sep 9.

Reference Type BACKGROUND
PMID: 26363834 (View on PubMed)

Park JB, Choi G, Chun EJ, Kim HJ, Park J, Jung JH, Lee MH, Otake H, Doh JH, Nam CW, Shin ES, De Bruyne B, Taylor CA, Koo BK. Computational fluid dynamic measures of wall shear stress are related to coronary lesion characteristics. Heart. 2016 Oct 15;102(20):1655-61. doi: 10.1136/heartjnl-2016-309299. Epub 2016 Jun 14.

Reference Type BACKGROUND
PMID: 27302987 (View on PubMed)

Lee JM, Choi G, Koo BK, Hwang D, Park J, Zhang J, Kim KJ, Tong Y, Kim HJ, Grady L, Doh JH, Nam CW, Shin ES, Cho YS, Choi SY, Chun EJ, Choi JH, Norgaard BL, Christiansen EH, Niemen K, Otake H, Penicka M, de Bruyne B, Kubo T, Akasaka T, Narula J, Douglas PS, Taylor CA, Kim HS. Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics. JACC Cardiovasc Imaging. 2019 Jun;12(6):1032-1043. doi: 10.1016/j.jcmg.2018.01.023. Epub 2018 Mar 14.

Reference Type BACKGROUND
PMID: 29550316 (View on PubMed)

Samady H, Eshtehardi P, McDaniel MC, Suo J, Dhawan SS, Maynard C, Timmins LH, Quyyumi AA, Giddens DP. Coronary artery wall shear stress is associated with progression and transformation of atherosclerotic plaque and arterial remodeling in patients with coronary artery disease. Circulation. 2011 Aug 16;124(7):779-88. doi: 10.1161/CIRCULATIONAHA.111.021824. Epub 2011 Jul 25.

Reference Type BACKGROUND
PMID: 21788584 (View on PubMed)

Lee JM, Choi G, Hwang D, Park J, Kim HJ, Doh JH, Nam CW, Na SH, Shin ES, Taylor CA, Koo BK. Impact of Longitudinal Lesion Geometry on Location of Plaque Rupture and Clinical Presentations. JACC Cardiovasc Imaging. 2017 Jun;10(6):677-688. doi: 10.1016/j.jcmg.2016.04.012. Epub 2016 Sep 21.

Reference Type BACKGROUND
PMID: 27665158 (View on PubMed)

Chang HJ, Lin FY, Lee SE, Andreini D, Bax J, Cademartiri F, Chinnaiyan K, Chow BJW, Conte E, Cury RC, Feuchtner G, Hadamitzky M, Kim YJ, Leipsic J, Maffei E, Marques H, Plank F, Pontone G, Raff GL, van Rosendael AR, Villines TC, Weirich HG, Al'Aref SJ, Baskaran L, Cho I, Danad I, Han D, Heo R, Lee JH, Rivzi A, Stuijfzand WJ, Gransar H, Lu Y, Sung JM, Park HB, Berman DS, Budoff MJ, Samady H, Shaw LJ, Stone PH, Virmani R, Narula J, Min JK. Coronary Atherosclerotic Precursors of Acute Coronary Syndromes. J Am Coll Cardiol. 2018 Jun 5;71(22):2511-2522. doi: 10.1016/j.jacc.2018.02.079.

Reference Type BACKGROUND
PMID: 29852975 (View on PubMed)

Williams MC, Kwiecinski J, Doris M, McElhinney P, D'Souza MS, Cadet S, Adamson PD, Moss AJ, Alam S, Hunter A, Shah ASV, Mills NL, Pawade T, Wang C, Weir McCall J, Bonnici-Mallia M, Murrills C, Roditi G, van Beek EJR, Shaw LJ, Nicol ED, Berman DS, Slomka PJ, Newby DE, Dweck MR, Dey D. Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART). Circulation. 2020 May 5;141(18):1452-1462. doi: 10.1161/CIRCULATIONAHA.119.044720. Epub 2020 Mar 16.

Reference Type BACKGROUND
PMID: 32174130 (View on PubMed)

Yang S, Koo BK, Hoshino M, Lee JM, Murai T, Park J, Zhang J, Hwang D, Shin ES, Doh JH, Nam CW, Wang J, Chen S, Tanaka N, Matsuo H, Akasaka T, Choi G, Petersen K, Chang HJ, Kakuta T, Narula J. CT Angiographic and Plaque Predictors of Functionally Significant Coronary Disease and Outcome Using Machine Learning. JACC Cardiovasc Imaging. 2021 Mar;14(3):629-641. doi: 10.1016/j.jcmg.2020.08.025. Epub 2020 Nov 25.

Reference Type BACKGROUND
PMID: 33248965 (View on PubMed)

Obuchowski NA, McClish DK. Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices. Stat Med. 1997 Jul 15;16(13):1529-42. doi: 10.1002/(sici)1097-0258(19970715)16:133.0.co;2-h.

Reference Type BACKGROUND
PMID: 9249923 (View on PubMed)

Alimohamadi Y, Sepandi M. Considering the design effect in cluster sampling. J Cardiovasc Thorac Res. 2019;11(1):78. doi: 10.15171/jcvtr.2019.14. Epub 2019 Feb 17. No abstract available.

Reference Type BACKGROUND
PMID: 31024678 (View on PubMed)

Collins GS, Ogundimu EO, Altman DG. Sample size considerations for the external validation of a multivariable prognostic model: a resampling study. Stat Med. 2016 Jan 30;35(2):214-26. doi: 10.1002/sim.6787. Epub 2015 Nov 9.

Reference Type BACKGROUND
PMID: 26553135 (View on PubMed)

Yang S, Jung JW, Park SH, Zhang J, Lee K, Hwang D, Lee KS, Na SH, Doh JH, Nam CW, Kim TH, Shin ES, Chun EJ, Choi SY, Kim HK, Hong YJ, Park HJ, Kim SY, Husic M, Lambrechtsen J, Jensen JM, Norgaard BL, Andreini D, Maurovich-Horvat P, Merkely B, Penicka M, de Bruyne B, Ihdayhid A, Ko B, Tzimas G, Leipsic J, Sanz J, Rabbat MG, Katchi F, Shah M, Tanaka N, Nakazato R, Asano T, Terashima M, Takashima H, Amano T, Sobue Y, Matsuo H, Otake H, Kubo T, Takahata M, Akasaka T, Kido T, Mochizuki T, Yokoi H, Okonogi T, Kawasaki T, Nakao K, Sakamoto T, Yonetsu T, Kakuta T, Yamauchi Y, Taylor CA, Bax JJ, Shaw LJ, Stone PH, Narula J, Koo BK. Prognostic Time Frame of Plaque and Hemodynamic Characteristics and Integrative Risk Prediction for Acute Coronary Syndrome. JACC Cardiovasc Imaging. 2025 Jul;18(7):784-795. doi: 10.1016/j.jcmg.2025.02.003. Epub 2025 Apr 23.

Reference Type DERIVED
PMID: 40272335 (View on PubMed)

Koo BK, Yang S, Jung JW, Zhang J, Lee K, Hwang D, Lee KS, Doh JH, Nam CW, Kim TH, Shin ES, Chun EJ, Choi SY, Kim HK, Hong YJ, Park HJ, Kim SY, Husic M, Lambrechtsen J, Jensen JM, Norgaard BL, Andreini D, Maurovich-Horvat P, Merkely B, Penicka M, de Bruyne B, Ihdayhid A, Ko B, Tzimas G, Leipsic J, Sanz J, Rabbat MG, Katchi F, Shah M, Tanaka N, Nakazato R, Asano T, Terashima M, Takashima H, Amano T, Sobue Y, Matsuo H, Otake H, Kubo T, Takahata M, Akasaka T, Kido T, Mochizuki T, Yokoi H, Okonogi T, Kawasaki T, Nakao K, Sakamoto T, Yonetsu T, Kakuta T, Yamauchi Y, Bax JJ, Shaw LJ, Stone PH, Narula J. Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome. JACC Cardiovasc Imaging. 2024 Sep;17(9):1062-1076. doi: 10.1016/j.jcmg.2024.03.015. Epub 2024 May 15.

Reference Type DERIVED
PMID: 38752951 (View on PubMed)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

NCT1869

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

PRE-DETERMINE Cohort Study
NCT01114269 ACTIVE_NOT_RECRUITING