Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr, Registry

Erasmus University

Status: Completed

Conditions: Coronary Artery Disease; Coronary Heart Disease

Study type: Observational

Funder types: Other; Industry

Identifiers

NCT02805621

Machine

Details and patient eligibility

About

Demonstrate in a large multicenter population the diagnostic performance of a pre-commercial on-site, local, CT angiography derived FFR algorithm in comparison to invasive FFR.

Full description

To retrospectively evaluate the diagnostic accuracy of FFRCT, in patients with known or suspected CAD. the investigators propose to do technical assessment of the software and evaluate how different parameters effect the outcome. Validate the FFTCT outcome by comparing the FFRCT values with invasive FFR values from retrospective patient data. To analyze the potential of FFRCT on decision making and prognosis.

Enrollment: 352 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Know or suspect coronary artery disease followed within 6 months by an invasive FFR measurement.

Exclusion criteria

• Cardiac event between coronary CT angiography and the invasive FFR procedure, noninterpretable coronary CT angiography image quality, or incomplete coronary CT angiography coverage.

Trial design

352 participants in 1 patient group

Subject

Description:

Patients with know or suspected coronary artery disease, who underwent both CT angiography and invasive coronary angiography including invasive FFR measurements.