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.
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.
Study Type
OBSERVATIONAL
Enrollment
350
Plaque morphology characterization on coronary CTA for predicting fractional flow reserve (FFRct)
Cardiovascular Medical Group of Southern California
Beverly Hills, California, United States
NOT_YET_RECRUITINGPiedmont Healthcare
Atlanta, Georgia, United States
NOT_YET_RECRUITINGParkview Health
Fort Wayne, Indiana, United States
Sensitivity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80
Per-vessel
Time frame: 1 day
Specificity of FFRct versus invasive FFR for detecting invasive FFR ≤ 0.80
Per-vessel
Time frame: 1 day
Sensitivity of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day
Specificity of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day
Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80
Per-vessel
Time frame: 1 day
Area under the receiver-operating characteristic curve (AUC) of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day
Accuracy of FFRct for detecting invasive FFR ≤ 0.80
Per-vessel
Time frame: 1 day
Accuracy of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day
Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80
Per-vessel
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Midwest Heart and Vascular Specialists
Overland Park, Kansas, United States
RECRUITINGValley Health System
Ridgewood, New Jersey, United States
NOT_YET_RECRUITINGCleveland Clinic
Cleveland, Ohio, United States
NOT_YET_RECRUITINGCentennial Heart
Nashville, Tennessee, United States
NOT_YET_RECRUITINGAscension Medical Group
Nashville, Tennessee, United States
NOT_YET_RECRUITINGUniversity of Virginia
Charlottesville, Virginia, United States
RECRUITINGTime frame: 1 day
Negative predictive value of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day
Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80
Per-vessel
Time frame: 1 day
Positive predictive value of FFRct for detecting invasive FFR ≤ 0.80
Per-patient
Time frame: 1 day