Validation of the “smart” minimum FFR Algorithm in an unselected all comer population of patients with intermediate coronary stenoses

Abstract

Using data from a commercial pressure wire system (St. Jude Medical) we previously developed an automated “smart” algorithm to determine a reproducible value for minimum FFR (smFFR) and confirmed that it correlated very closely with measurements made off-line by experienced coronary physiology core laboratories. In this study we used the same “smart” minimum algorithm to analyze data derived from a different, commercial pressure wire system (Philips Volcano) and compared the values obtained to both operator-defined steady state FFR and the online automated minimum FFR reported by the pressure wire analyser. For this analysis, we used the data collected during the VERIFY 2 study (Hennigan et al. in Circ Cardiovasc Interv, doi:10.1161/CIRCINTERVENTIONS.116.004016) in which we measured FFR in 257 intermediate coronary stenoses (mean DS 48%) in 197 patients. Maximal hyperaemia was induced using intravenous adenosine (140 mcg/kg/min). We recorded both the online minimum FFR generated by the analyser and the operator-reported steady state FFR. Subsequently, the raw pressure tracings were coded, anonymised and 256/257 were subjected to further off-line analysis using the smart minimum FFR (smFFR) algorithm. The operator-defined steady state FFR correlated well with smFFR: r = 0.988 (p < 0.001), average bias 0.008 (SD 0.014), 95% limits of agreement −0.020 to 0.036. The online automated minimum FFR also correlated well with the smFFR: r = 0.998 (p < 0.001), average bias 0.004 (SD 0.006), 95% limits of agreement −0.016 to 0.008. Finally, the online automated minimum FFR correlated well the operator-reported steady state FFR: r = 0.988 (p < 0.001), average bias 0.012 (SD 0.014), 95% limits of agreement −0.039 to 0.015. In 95% of lesions studied (244/256), the operator reported steady-state FFR, smFFR, and online automated minimum FFR agreed with each other to within 0.04, which is within the previously reported test/retest limits of agreement of FFR reported by an experienced core lab. Disagreements >0.05 among methods were rare but in these cases the two automated algorithms almost always agreed with each other rather than with the operator-reported value. Within the VERIFY 2 dataset, experienced operators reported a similar FFR value to both an online automated minimum (Philips Volcano) and off-line “smart” minimum computer algorithm. Thus, treatment decisions and clinical studies using either method will produce nearly identical results.