Jelmer Westra1, Shengxian Tu2, Gianluca Campo3,4, Shubin Qiao5, Hitoshi Matsuo6, Xinkai Qu7, Lukasz Koltowski8, Yunxiao Chang2, Tommy Liu9, Junqing Yang10, Birgitte Krogsgaard Andersen1, Ashkan Eftekhari1, Evald Høj Christiansen1, Javier Escaned11, William Wijns12, Bo Xu5, Niels Ramsing Holm1. 1. Department of Cardiology, Aarhus University Hospital, Skejby, Denmark. 2. School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. 3. Cardiovascular Institute, Azienda Ospedaliero-Universitaria di Ferrara, Cona (FE), Italy. 4. Maria Cecilia Hospital, GVM Care & Research, Cotignola (RA), Italy. 5. Fu Wai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Beijing, China. 6. Department of Cardiovascular Medicine, Gifu Heart Center, Gifu City, Japan. 7. Huadong Hospital Affiliated to Fudan University, Shanghai, China. 8. 1st Department of Cardiology, Medical University of Warsaw, Warsaw, Poland. 9. Department of Cardiology, Hagaziekenhuis, The Hague, The Netherlands. 10. Guangdong General Hospital, Guangzhou, China. 11. Department of Cardiology, Hospital Clinico San Carlos, Madrid, Spain. 12. The Lambe Institute for Translational Medicine and Curam, National University of Ireland Galway, Ireland.
Abstract
OBJECTIVES: We aimed to provide robust performance estimates for quantitative flow ratio (QFR) in assessment of intermediary coronary lesions. BACKGROUND: Angiography-based functional lesion assessment by QFR may appear as a cost saving and safe approach to expand the use of physiology-guided percutaneous coronary interventions. QFR was proven feasible and showed good diagnostic performance in mid-sized off-line and on-line studies with fractional flow reserve (FFR) as reference standard. METHODS: We performed a collaborative individual patient-data meta-analysis of all available prospective studies with paired assessment of QFR and FFR using the CE-marked QFR application. The main outcome was agreement of QFR and FFR using a two-step analysis strategy with a multilevel mixed model accounting for study and center level variation. RESULTS: Of 16 studies identified, four studies had prospective enrollment and provided patient level data reaching a total of 819 patients and 969 vessels with paired FFR and QFR: FAVOR Pilot (n = 73); WIFI II (n = 170); FAVOR II China (n = 304) and FAVOR II Europe-Japan (n = 272). We found an overall agreement (mean difference 0.009 ± 0.068, I2 = 39.6) of QFR with FFR. The diagnostic performance was sensitivity 84% (95%CI: 77-90, I2 = 70.1), specificity 88% (95%CI: 84-91, I2 = 60.1); positive predictive value 80% (95%CI: 76-85, I2 = 33.4), and negative predictive value 95% (95%CI: 93-96, I2 = 75.9). CONCLUSIONS: Diagnostic performance of QFR was good with FFR as reference in this meta-analysis of high quality studies. QFR could provide an easy, safe, and cost-effective solution for functional evaluation of coronary artery stenosis.
OBJECTIVES: We aimed to provide robust performance estimates for quantitative flow ratio (QFR) in assessment of intermediary coronary lesions. BACKGROUND: Angiography-based functional lesion assessment by QFR may appear as a cost saving and safe approach to expand the use of physiology-guided percutaneous coronary interventions. QFR was proven feasible and showed good diagnostic performance in mid-sized off-line and on-line studies with fractional flow reserve (FFR) as reference standard. METHODS: We performed a collaborative individual patient-data meta-analysis of all available prospective studies with paired assessment of QFR and FFR using the CE-marked QFR application. The main outcome was agreement of QFR and FFR using a two-step analysis strategy with a multilevel mixed model accounting for study and center level variation. RESULTS: Of 16 studies identified, four studies had prospective enrollment and provided patient level data reaching a total of 819 patients and 969 vessels with paired FFR and QFR: FAVOR Pilot (n = 73); WIFI II (n = 170); FAVOR II China (n = 304) and FAVOR II Europe-Japan (n = 272). We found an overall agreement (mean difference 0.009 ± 0.068, I2 = 39.6) of QFR with FFR. The diagnostic performance was sensitivity 84% (95%CI: 77-90, I2 = 70.1), specificity 88% (95%CI: 84-91, I2 = 60.1); positive predictive value 80% (95%CI: 76-85, I2 = 33.4), and negative predictive value 95% (95%CI: 93-96, I2 = 75.9). CONCLUSIONS: Diagnostic performance of QFR was good with FFR as reference in this meta-analysis of high quality studies. QFR could provide an easy, safe, and cost-effective solution for functional evaluation of coronary artery stenosis.
Authors: Federico Marin; Roberto Scarsini; Dimitrios Terentes-Printzios; Rafail A Kotronias; Flavio Ribichini; Adrian P Banning; Giovanni Luigi De Maria Journal: Curr Cardiol Rev Date: 2022
Authors: Martin Sejr-Hansen; Jelmer Westra; Simon Winther; Shengxian Tu; Louise Nissen; Lars Gormsen; Steffen E Petersen; June Ejlersen; Christin Isaksen; Hans Erik Bøtker; Morten Bøttcher; Evald H Christiansen; Niels Ramsing Holm Journal: Int J Cardiovasc Imaging Date: 2019-11-19 Impact factor: 2.357