Takuya Mizukami1, Kaoru Tanaka2, Jeroen Sonck3, Bert Vandeloo4, Bram Roosens4, Stijn Lochy4, Jean Francois Argacha4, Danny Schoors4, Hiroshi Suzuki5, Dries Belsack2, Daniele Andreini6, Emanuelle Barbato7, Johan De Mey2, Bernard De Bruyne8, Bernard Cosyns4, Carlos Collet9. 1. Cardiology, Centrum voor Hart- en Vaatziekten, Universitair Ziekenhuis Brussel, Brussels, Belgium; Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium; Department of Cardiology, Showa University Fujigaoka Hospital, Kanagawa, Japan. 2. Department of Radiology, Universitair Ziekenhuis Brussel, Brussels, Belgium. 3. Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium; Department of Advanced Biomedical Sciences, University of Naples, Federico II, Naples, Italy. 4. Cardiology, Centrum voor Hart- en Vaatziekten, Universitair Ziekenhuis Brussel, Brussels, Belgium. 5. Department of Cardiology, Showa University Fujigaoka Hospital, Kanagawa, Japan. 6. Centro Cardiologico Monzino, IRCCS, Milan, Italy; Department of Cardiovascular Sciences and Community Health, University of Milan, Milan, Italy. 7. Department of Advanced Biomedical Sciences, University of Naples, Federico II, Naples, Italy. 8. Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium. 9. Cardiovascular Center Aalst, OLV Clinic, Aalst, Belgium. Electronic address: carloscollet@gmail.com.
Abstract
AIMS: Fractional flow reserve (FFR) pullback allows to assess the distribution of pressure loss along the coronary vessels. FFR derived from CT (FFRCT) provides a virtual pullback curve that may also aid in the assessment of the distribution of epicardial coronary resistance in the non-invasive setting. The present study aims to determine the accuracy of the virtual FFRCT pullback curve using a motorized invasive FFR pullback as reference in patients with stable coronary artery disease. METHODS AND RESULTS: FFR values were extracted from coronary vessels at approximately 1 mm to generate pullback curves. Invasive motorized FFR pullbacks were acquired using a dedicated device at a speed of 1 mm/s. A total of 3172 matched FFRCT and FFR values were obtained in 24 vessels. The correlation coefficient between FFRCT and FFR was 0.76 (95%CI 0.75 to 0.78; p < 0.001). The area under the pullback curve was similar between FFRCT and invasive FFR (79.0 ± 16.1 vs. 85.3 ± 16.4, p = 0.097). The mean difference in lesion gradient between FFRCT and FFR was -0.07 (LOA -0.26 to 0.13) whereas in non-obstructive segments was -0.01 (LOA -0.06 to 0.05). CONCLUSION: The evaluation of epicardial coronary resistance using coronary CT angiography with FFRCT was feasible. FFRCT virtual pullback appears to be accurate for the evaluation of pressure gradients. FFRCT has the potential to identify the pathophysiological pattern of coronary artery disease in the non-invasive setting.
AIMS: Fractional flow reserve (FFR) pullback allows to assess the distribution of pressure loss along the coronary vessels. FFR derived from CT (FFRCT) provides a virtual pullback curve that may also aid in the assessment of the distribution of epicardial coronary resistance in the non-invasive setting. The present study aims to determine the accuracy of the virtual FFRCT pullback curve using a motorized invasive FFR pullback as reference in patients with stable coronary artery disease. METHODS AND RESULTS: FFR values were extracted from coronary vessels at approximately 1 mm to generate pullback curves. Invasive motorized FFR pullbacks were acquired using a dedicated device at a speed of 1 mm/s. A total of 3172 matched FFRCT and FFR values were obtained in 24 vessels. The correlation coefficient between FFRCT and FFR was 0.76 (95%CI 0.75 to 0.78; p < 0.001). The area under the pullback curve was similar between FFRCT and invasive FFR (79.0 ± 16.1 vs. 85.3 ± 16.4, p = 0.097). The mean difference in lesion gradient between FFRCT and FFR was -0.07 (LOA -0.26 to 0.13) whereas in non-obstructive segments was -0.01 (LOA -0.06 to 0.05). CONCLUSION: The evaluation of epicardial coronary resistance using coronary CT angiography with FFRCT was feasible. FFRCT virtual pullback appears to be accurate for the evaluation of pressure gradients. FFRCT has the potential to identify the pathophysiological pattern of coronary artery disease in the non-invasive setting.
Authors: Todd C Villines; Subhi J Al'Aref; Daniele Andreini; Marcus Y Chen; Andrew D Choi; Carlo N De Cecco; Damini Dey; James P Earls; Maros Ferencik; Heidi Gransar; Harvey Hecht; Jonathon A Leipsic; Michael T Lu; Mohamed Marwan; Pál Maurovich-Horvat; Edward Nicol; Gianluca Pontone; Jonathan Weir-McCall; Seamus P Whelton; Michelle C Williams; Armin Arbab-Zadeh; Gudrun M Feuchtner Journal: J Cardiovasc Comput Tomogr Date: 2021-02-22
Authors: Sakura Nagumo; Carlos Collet; Bjarne L Norgaard; Hiromasa Otake; Brian Ko; Bon-Kwon Koo; Jonathon Leipsic; Daniele Andreini; Ward Heggermont; Jesper M Jensen; Yu Takahashi; Abdul Ihdayhid; Zinlong Zhang; Emanuele Barbato; Michael Maeng; Takuya Mizukami; Jozef Bartunek; Adam Updegrove; Martin Penicka; Campbell Rogers; Charles Taylor; Bernard De Bruyne; Jeroen Sonck Journal: Clin Cardiol Date: 2021-03-03 Impact factor: 2.882