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. 2024 Nov 25;11:1468888. doi: 10.3389/fcvm.2024.1468888

Table 1.

Comparison of various commercially available angiography-derived FFR software.

Company µFR QFR FFR angio vFFR caFFR Angio-FFR AutocathFFR
Pulse medical Medis/Pulse Medical CathWorks Pie Medical Rainmed Siemens Medhub Ltd
Estimated FFR FFR FFR FFR FFR FFR FFR
Required angio projections 1 2 projections >25° apart 2 projections >30° apart 2 projections 2 projections >30° apart 2 projections >30° apart 2 projections
Require pressure data No No No Needed Needed No No
Side branches Incorporated Not incorporated Incorporated Not incorporated Not incorporated Incorporated NA
Computation model Kirkeeide Lance Gould equation Electric circuit model Simplified
Navier–Stokes
Simplified
Navier–Stokes
AI based AI based
Studies Tu et al. FAVOR pilot
FAVOR II
China
FAVOR II EJ
FAVOR III
FAST-FFR FAST
FAST II
FAST-FFR
FLASH II
Omori et al. Ben-Assa E et al. (188)
C-statistics for predicting FFR ≤ 0.8 0.97 0.92–0.96 0.94 0.93 0.98 0.90 0.93
Mean time to computation 67 s 4.36 min 2.7 min NA 4.5 min NA 45 s

AI, artificial intelligence; caFFR, coronary angiography-based fractional flow reserve; FAVOR, functional diagnostic accuracy of QFR in online assessment of coronary stenosis; FAST, fast assessment of stenosis severity; FFR, fractional flow reserve; µFR, Murray law-based fractional flow ratio; NA, not available; QFR, quantitative flow ratio; vFFR, vessel fractional flow reserve.