AIMS: The aim of this study was to develop a simplified model of FFR calculation (FFRsim) derived from three-dimensional (3D) coronary angiographic data and classic fluid dynamic equations without using finite element analysis. METHODS AND RESULTS: Intracoronary pressure measurements were performed by pressure wire sensors. The lumens of the interrogated vessel segments were reconstructed in 3D. The coronary artery volumetric flow was calculated based on the velocity of the contrast material. Pressure gradients were computed by classic fluid dynamic equations. The diagnostic power of the simplified computation of the FFR (FFRsim) was assessed by comparing the results with standard invasive FFR measurements (FFRmeas) in 68 vessels with a single stenosis. We found a strong correlation between the FFRsim and the FFRmeas (r=0.86, p<0.0001). The sensitivity and specificity for predicting the abnormal FFR of ≤0.80 (indicating haemodynamically significant stenosis) were 90% and 100%, respectively. The area under the curve (AUC) was 0.96. To achieve 100% negative and positive predictive values we defined the FFRsim >0.88 and the FFRsim ≤0.8 ranges. In our patient population, these ranges were found in 69% of the cases. CONCLUSIONS: According to our simplified model, the invasive FFR measurement can be omitted without misclassification in pre-specified ranges of the calculated FFRsim.
AIMS: The aim of this study was to develop a simplified model of FFR calculation (FFRsim) derived from three-dimensional (3D) coronary angiographic data and classic fluid dynamic equations without using finite element analysis. METHODS AND RESULTS: Intracoronary pressure measurements were performed by pressure wire sensors. The lumens of the interrogated vessel segments were reconstructed in 3D. The coronary artery volumetric flow was calculated based on the velocity of the contrast material. Pressure gradients were computed by classic fluid dynamic equations. The diagnostic power of the simplified computation of the FFR (FFRsim) was assessed by comparing the results with standard invasive FFR measurements (FFRmeas) in 68 vessels with a single stenosis. We found a strong correlation between the FFRsim and the FFRmeas (r=0.86, p<0.0001). The sensitivity and specificity for predicting the abnormal FFR of ≤0.80 (indicating haemodynamically significant stenosis) were 90% and 100%, respectively. The area under the curve (AUC) was 0.96. To achieve 100% negative and positive predictive values we defined the FFRsim >0.88 and the FFRsim ≤0.8 ranges. In our patient population, these ranges were found in 69% of the cases. CONCLUSIONS: According to our simplified model, the invasive FFR measurement can be omitted without misclassification in pre-specified ranges of the calculated FFRsim.
Authors: Balázs Tar; Csaba Jenei; Áron Üveges; Gábor Tamás Szabó; András Ágoston; Csaba András Dézsi; András Komócsi; Dániel Czuriga; Attila Juhász; Zsolt Kőszegi Journal: Cardiol J Date: 2020-11-03 Impact factor: 2.737
Authors: Balázs Tar; András Ágoston; Áron Üveges; Gábor Tamás Szabó; Tibor Szűk; András Komócsi; Dániel Czuriga; Benjamin Csippa; György Paál; Zsolt Kőszegi Journal: J Pers Med Date: 2022-05-12
Authors: Gábor Tamás Szabó; Áron Üveges; Balázs Tar; András Ágoston; Azzaya Dorj; Csaba Jenei; Rudolf Kolozsvári; Benjamin Csippa; Dániel Czuriga; Zsolt Kőszegi Journal: J Clin Med Date: 2021-04-28 Impact factor: 4.241
Authors: Hazel Arfah Haley; Mina Ghobrial; Paul D Morris; Rebecca Gosling; Gareth Williams; Mark T Mills; Tom Newman; Vignesh Rammohan; Giulia Pederzani; Patricia V Lawford; Rodney Hose; Julian P Gunn Journal: Front Cardiovasc Med Date: 2021-10-22