Background The influence of computed tomography (CT) reconstruction algorithms on the
performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR ML) …

To evaluate the impact of an iterative reconstruction (IR) algorithm (advanced modeled
iterative reconstruction, ADMIRE) on machine learning-based coronary computed …

Background Compared with invasive fractional flow reserve (FFR), coronary CT
angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based …

Background: Coronary computed tomographic angiography (CTA) is a reliable modality to
detect coronary artery disease. However, CTA generally overestimates stenosis severity …

Purpose To compare two technical approaches for determination of coronary computed
tomography (CT) angiography–derived fractional flow reserve (FFR)—FFR derived from …

Background Fractional flow reserve derived from computed tomography (CT-FFR) can be
used to noninvasively evaluate the functions of coronary arteries and has been widely …

Background: Machine-learning-based computed-tomography-derived fractional flow reserve
(CT-FFRML) obtains a hemodynamic index in coronary arteries. We examined whether it …

Aims To evaluate the impact of coronary artery calcium (CAC) score, minimal lumen area
(MLA), and length of coronary artery stenosis on the diagnostic performance of the machine …

Aims Although deep-learning algorithms have been used to compute fractional flow reserve
(FFR) from coronary computed tomography angiography (CCTA), no study has achieved …

AIM To validate the computed tomography (CT)-derived fractional flow reserve (FFR CT) that
was computed by new, fast, automatic software and to compare the diagnostic accuracy …