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Clinical Trial Details — Status: Active, not recruiting

Administrative data

NCT number NCT03591328
Other study ID # NCT1869
Secondary ID
Status Active, not recruiting
Phase
First received
Last updated
Start date July 9, 2018
Est. completion date December 31, 2022

Study information

Verified date August 2022
Source Seoul National University Hospital
Contact n/a
Is FDA regulated No
Health authority
Study type Observational [Patient Registry]

Clinical Trial Summary

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.


Description:

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.


Recruitment information / eligibility

Status Active, not recruiting
Enrollment 429
Est. completion date December 31, 2022
Est. primary completion date September 30, 2022
Accepts healthy volunteers No
Gender All
Age group N/A and older
Eligibility 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 for Patient enrollment 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. 8. Patients with unstable angina without evidence of plaque rupture Additional exclusion criteria for Computational Fluid Dynamics 9. Poor quality CCTA images unsuitable for CFD and plaque analysis 10. No unprocessed CCTA data

Study Design


Intervention

Diagnostic Test:
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.

Locations

Country Name City State
Korea, Republic of Seoul National University Hospital Seoul

Sponsors (40)

Lead Sponsor Collaborator
Seoul National University Hospital Aarhus University Hospital, Aichi Medical University, Chosun University Hospital, Chungnam National University Hospital, Ehime University Graduate School of Medicine, Emory University, Gifu Heart Center, Imperial College London, Inje University Ilsan Paik Hospital, Keimyung University Dongsan Medical Center, Kobe University Hospital, Leiden University, Loyola University, Monash Heart, Monzino Cardiology Center, MOUNT SINAI HOSPITAL, National Cerebral and Cardiovascular Center, Odense University Hospital, OLV Hospital, Oxford University Hospital, Saiseikai Kumamoto Hospital, Semmelweis University, Seoul National University Bundang Hospital, Seoul National University Hospital Healthcare System Gangnam Center, Shin Koga Hospital, St. Luke's International Hospital, St. Mary's hostpital, Tokai University, Tokyo Medical Dental University, Tokyo Medical University Hachioji Medical Center, Toyohashi Heart Center, Tsuchiura Kyodo Hospital, Ulsan Hospital, Ulsan University Hospital, University of British Columbia, University of Milan, Wakayama Medical University, Weil Cornell Medical College, West Penn Allegheny Health System

Country where clinical trial is conducted

Korea, Republic of, 

References & Publications (18)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

Koskinas KC, Ughi GJ, Windecker S, Tearney GJ, Räber 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. Review. — View Citation

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. — View Citation

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, Nørgaard 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. — View Citation

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. Review. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Review. — View Citation

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. — View Citation

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. — View Citation

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. Review. — View Citation

* Note: There are 18 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary discrimination index of prediction model discrimination index of prediction model 1 months - 3 years
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