Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II (EMERALD II) Study (EMERALD II)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Locations
-
-
-
Seoul, Korea, Republic of
- Seoul National University Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients who presented with ACS* and underwent invasive coronary angiography with identifiable culprit lesion
- 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.
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 for Patient enrollment
- Patients with ACS without clear evidence of culprit lesion
- Patients with stents in two or more vessel territories prior to CCTA
- Poor quality of CCTA which is unsuitable for plaque and CFD analysis
- Patients with ACS culprit lesion in a stented segment
- Patients with previous history of coronary artery bypass graft surgery
- Patients with revascularization after CCTA and before ACS event (*Patients with elective PCI for 1 vessel within 3 month after CCTA can be enrolled.
- Secondary ACS due to other general medical conditions, such as sepsis, arrhythmia, bleeding, etc.
- Patients with unstable angina without evidence of plaque rupture Additional exclusion criteria for Computational Fluid Dynamics
- Poor quality CCTA images unsuitable for CFD and plaque analysis
- No unprocessed CCTA data
Study Plan
How is the study designed?
Design Details
- Observational Models: Case-Control
- Time Perspectives: Other
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Culprit
Plaques which is related with acute coronary syndrome
|
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
|
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. |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
discrimination index of prediction model
Time Frame: 1 months - 3 years
|
discrimination index of prediction model
|
1 months - 3 years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Chair: Bon-Kwon Koo, MD,PhD, Seoul National University Hospital
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
- 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.
- 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. Erratum In: N Engl J Med. 2011 Nov 24;365(21):2040.
- 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.
- 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. Erratum In: Eur Heart J. 2020 Jan 14;41(3):393.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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. Erratum In: JACC Cardiovasc Imaging. 2019 Nov;12(11 Pt 1):2288-2289.
- 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.
- 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.
- 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.
- 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.
- 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.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- NCT1869
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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