ELUCIDATE FFRct Study

Coronary Artery Disease Clinical Trial

Official title:

The ELUCIDATE FFRct Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06018194
• Other study ID #: 3-ST-03-03
• Status: Recruiting
• Start date: September 1, 2023
• Est. completion date: July 31, 2024

Study information

• Verified date: February 2024
• Source: Elucid Bioimaging Inc.
• Contact: Todd C Villines, MD
• Phone: 978-468-0508
• Email: todd.villines[@]elucid.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The goal of this study is to evaluate the diagnostic accuracy of a novel plaque-based coronary CT angiography (CCTA) fractional flow reserve (FFRct) software device for the estimation of invasive fractional flow reserve (FFR).

Researchers will compare the Elucid plaque-based FFRct analysis to invasively measured FFR in patients who have previously undergone CCTA and invasively assessed FFR.

Description:

Invasive fractional flow reserve is a clinically validated measure of lesion-specific ischemia and is preferred over visual estimation of diameter stenosis for clinical decision-making regarding coronary revascularization in patients with stable clinical presentations. Fractional flow reserve derived from coronary computed tomography angiography (FFRct) using computational fluid dynamic (CFD)-based software has been shown to be a reasonably accurate estimate of invasive FFR and is included in contemporary guidelines as a decision-tool for management of patients with intermediate stenosis on CCTA. However, CFD-based FFRct is calculated based predominately on detailed coronary lumen geometry. It is understood that the burden and type of coronary atherosclerosis, in addition to lumen geometry, significantly impacts the vasodilatory capacity of the coronary endothelium.

Preliminary studies suggest that invasive FFR can be accurately estimated based on the quantification of coronary plaque burden and the assessment of plaque composition. Previously, the investigators have demonstrated that a novel plaque-based FFRct approach, using a histologically validated software (ElucidVivoTM) for the measurement of plaque morphology (volume, plaque risk characteristics, and stenosis) to train a deep-learning model, was shown to be accurate and superior to lumen stenosis for predicting invasive FFR in a single-site feasibility study.

In this study, the investigators seek to assess the diagnostic accuracy of the Elucid plaque-based FFRct software to estimate invasive FFR in patients at multiple centers.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 350
• Est. completion date: July 31, 2024
• Est. primary completion date: July 31, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Adults >=18 years with at least one 30-90% stenosis on CCTA (>64- detector row) performed within 60 days of undergoing invasive FFR.

Exclusion Criteria:

• History of coronary revascularization with coronary artery bypass graft (CABG) surgery and/or percutaneous coronary intervention (PCI) (stent or balloon angioplasty) prior to CCTA and invasive FFR.

• History of myocardial infarction prior to CCTA and invasive FFR.

• Known complex congenital heart disease.

• Existing pacemaker or internal defibrillator lead implantation(s).

• Existing prosthetic heart valve.

• Absence of CCTA Digital Imaging and Communications in Medicine (DICOM) data for analysis.

• Absence of invasive coronary angiography imaging or adequate description defining the position of the invasive FFR wire location.

• Poor CCTA image quality that does not meet Elucid image processing requirements for plaque and FFRct.

• Absence of study date for CCTA or invasive FFR.

• Interval clinical myocardial infarction, diagnosis of decompensated heart failure, stroke, or coronary revascularization procedure between CCTA and invasive FFR.

• Non-diagnostic CCTA or invasive FFR. Studies where the results of the study were deemed non-diagnostic for clinical decision-making will be excluded.

• CCTA or invasive FFR studies performed prior to 1 January 2016.

Related Conditions & MeSH terms

• Coronary Artery Disease

Intervention

Device:
• ElucidVivo
Plaque morphology characterization on coronary CTA for predicting fractional flow reserve (FFRct)

Locations

Country	Name	City	State
United States	Piedmont Healthcare	Atlanta	Georgia
United States	Cardiovascular Medical Group of Southern California	Beverly Hills	California
United States	University of Virginia	Charlottesville	Virginia
United States	Cleveland Clinic	Cleveland	Ohio
United States	Parkview Health	Fort Wayne	Indiana
United States	Ascension Medical Group	Nashville	Tennessee
United States	Centennial Heart	Nashville	Tennessee
United States	Midwest Heart and Vascular Specialists	Overland Park	Kansas
United States	Valley Health System	Ridgewood	New Jersey

Sponsors (2)

Lead Sponsor	Collaborator
Elucid Bioimaging Inc.	Lundquist Institute at Harbor-UCLA Medical Center

Country where clinical trial is conducted

United States, 

References & Publications (9)

Ahmadi A, Stone GW, Leipsic J, Serruys PW, Shaw L, Hecht H, Wong G, Norgaard BL, O'Gara PT, Chandrashekhar Y, Narula J. Association of Coronary Stenosis and Plaque Morphology With Fractional Flow Reserve and Outcomes. JAMA Cardiol. 2016 Jun 1;1(3):350-7. doi: 10.1001/jamacardio.2016.0263. — View Citation

Buckler AJ, Sakamoto A, Pierre SS, Virmani R, Budoff MJ. Virtual pathology: Reaching higher standards for noninvasive CTA tissue characterization capability by using histology as a truth standard. Eur J Radiol. 2023 Feb;159:110686. doi: 10.1016/j.ejrad.2022.110686. Epub 2022 Dec 31. — View Citation

Diaz-Zamudio M, Dey D, Schuhbaeck A, Nakazato R, Gransar H, Slomka PJ, Narula J, Berman DS, Achenbach S, Min JK, Doh JH, Koo BK. Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions. Radiology. 2015 Aug;276(2):408-15. doi: 10.1148/radiol.2015141648. Epub 2015 Apr 17. — View Citation

Gulati M, Levy PD, Mukherjee D, Amsterdam E, Bhatt DL, Birtcher KK, Blankstein R, Boyd J, Bullock-Palmer RP, Conejo T, Diercks DB, Gentile F, Greenwood JP, Hess EP, Hollenberg SM, Jaber WA, Jneid H, Joglar JA, Morrow DA, O'Connor RE, Ross MA, Shaw LJ. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2021 Nov 30;144(22):e368-e454. doi: 10.1161/CIR.0000000000001029. Epub 2021 Oct 28. Erratum In: Circulation. 2021 Nov 30;144(22):e455. Circulation. 2023 Dec 12;148(24):e281. — View Citation

Lawton JS, Tamis-Holland JE, Bangalore S, Bates ER, Beckie TM, Bischoff JM, Bittl JA, Cohen MG, DiMaio JM, Don CW, Fremes SE, Gaudino MF, Goldberger ZD, Grant MC, Jaswal JB, Kurlansky PA, Mehran R, Metkus TS Jr, Nnacheta LC, Rao SV, Sellke FW, Sharma G, Yong CM, Zwischenberger BA. 2021 ACC/AHA/SCAI Guideline for Coronary Artery Revascularization: Executive Summary: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022 Jan 18;145(3):e4-e17. doi: 10.1161/CIR.0000000000001039. Epub 2021 Dec 9. Erratum In: Circulation. 2022 Mar 15;145(11):e771. — View Citation

Lin A, van Diemen PA, Motwani M, McElhinney P, Otaki Y, Han D, Kwan A, Tzolos E, Klein E, Kuronuma K, Grodecki K, Shou B, Rios R, Manral N, Cadet S, Danad I, Driessen RS, Berman DS, Norgaard BL, Slomka PJ, Knaapen P, Dey D. Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve-Defined Ischemia and Impaired Myocardial Blood Flow. Circ Cardiovasc Imaging. 2022 Oct;15(10):e014369. doi: 10.1161/CIRCIMAGING.122.014369. Epub 2022 Oct 13. — View Citation

Stuijfzand WJ, van Rosendael AR, Lin FY, Chang HJ, van den Hoogen IJ, Gianni U, Choi JH, Doh JH, Her AY, Koo BK, Nam CW, Park HB, Shin SH, Cole J, Gimelli A, Khan MA, Lu B, Gao Y, Nabi F, Nakazato R, Schoepf UJ, Driessen RS, Bom MJ, Thompson R, Jang JJ, Ridner M, Rowan C, Avelar E, Genereux P, Knaapen P, de Waard GA, Pontone G, Andreini D, Al-Mallah MH, Lu Y, Berman DS, Narula J, Min JK, Bax JJ, Shaw LJ; CREDENCE Investigators. Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial. JAMA Cardiol. 2020 Dec 1;5(12):1338-1348. doi: 10.1001/jamacardio.2020.3409. — View Citation

Tesche C, De Cecco CN, Caruso D, Baumann S, Renker M, Mangold S, Dyer KT, Varga-Szemes A, Baquet M, Jochheim D, Ebersberger U, Bayer RR 2nd, Hoffmann E, Steinberg DH, Schoepf UJ. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun;10(3):199-206. doi: 10.1016/j.jcct.2016.03.002. Epub 2016 Mar 10. — View Citation

Varga-Szemes A, Schoepf UJ, Maurovich-Horvat P, Wang R, Xu L, Dargis DM, Emrich T, Buckler AJ. Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve. Int J Cardiol. 2021 May 15;331:307-315. doi: 10.1016/j.ijcard.2021.01.040. Epub 2021 Jan 30. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Sensitivity of FFRct versus invasive FFR for detecting invasive FFR = 0.80	Per-vessel	1 day
Primary	Specificity of FFRct versus invasive FFR for detecting invasive FFR = 0.80	Per-vessel	1 day
Secondary	Sensitivity of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day
Secondary	Specificity of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day
Secondary	Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR = 0.80	Per-vessel	1 day
Secondary	Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day
Secondary	Accuracy of FFRct for detecting invasive FFR = 0.80	Per-vessel	1 day
Secondary	Accuracy of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day
Secondary	Negative predictive value of FFRct for detecting invasive FFR = 0.80	Per-vessel	1 day
Secondary	Negative predictive value of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day
Secondary	Positive predictive value of FFRct for detecting invasive FFR = 0.80	Per-vessel	1 day
Secondary	Positive predictive value of FFRct for detecting invasive FFR = 0.80	Per-patient	1 day