BACKGROUND:Fractional flow reserve derived from computed tomography angiography (FFRCT) is a noninvasive method for diagnosis of ischemic coronary lesions. To date, the diagnostic performance of FFRCT for lesions of intermediate stenosis severity remains unexamined. METHODS AND RESULTS:Among 407 vessels from 252 patients at 17 centers who underwent CT, FFRCT, invasive coronary angiography, and invasive FFR, we identified 150 vessels of intermediate stenosis by CT, defined as 30% to 69% stenosis. FFRCT, FFR, and CT were interpreted in blinded fashion by independent core laboratories. FFRCT and FFR ≤0.80 were considered hemodynamically significant, whereas CT stenosis ≥50% was considered obstructive. Diagnostic performance of FFRCT versus CT was assessed for accuracy, sensitivity, specificity, positive predictive values, and negative predictive values. Area under the receiver operating characteristic curve and net reclassification improvement were evaluated. For lesions of intermediate stenosis severity, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of FFRCT were 71%, 74%, 67%, 41%, and 90%, whereas accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT stenosis were 63%, 34%, 72%, 27%, and 78%. FFRCT demonstrated superior discrimination compared with CT stenosis on per-patient (area under the receiver operating characteristic curve, 0.81 versus 0.50; P=0.0001) and per-vessel basis (area under the receiver operating characteristic curve, 0.79 versus 0.53; P<0.0001). FFRCT demonstrated significant reclassification of CT stenosis for lesion-specific ischemia (net reclassification improvement, 0.45; 95% confidence interval, 0.25-0.65; P=0.01). CONCLUSIONS:FFRCT possesses high diagnostic performance for diagnosis of ischemic for lesions of intermediate stenosis severity. Notably, the high sensitivity and negative predictive value suggest the ability of FFRCT to effectively rule out intermediate lesions that cause ischemia.
RCT Entities:
BACKGROUND: Fractional flow reserve derived from computed tomography angiography (FFRCT) is a noninvasive method for diagnosis of ischemic coronary lesions. To date, the diagnostic performance of FFRCT for lesions of intermediate stenosis severity remains unexamined. METHODS AND RESULTS: Among 407 vessels from 252 patients at 17 centers who underwent CT, FFRCT, invasive coronary angiography, and invasive FFR, we identified 150 vessels of intermediate stenosis by CT, defined as 30% to 69% stenosis. FFRCT, FFR, and CT were interpreted in blinded fashion by independent core laboratories. FFRCT and FFR ≤0.80 were considered hemodynamically significant, whereas CT stenosis ≥50% was considered obstructive. Diagnostic performance of FFRCT versus CT was assessed for accuracy, sensitivity, specificity, positive predictive values, and negative predictive values. Area under the receiver operating characteristic curve and net reclassification improvement were evaluated. For lesions of intermediate stenosis severity, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of FFRCT were 71%, 74%, 67%, 41%, and 90%, whereas accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of CT stenosis were 63%, 34%, 72%, 27%, and 78%. FFRCT demonstrated superior discrimination compared with CT stenosis on per-patient (area under the receiver operating characteristic curve, 0.81 versus 0.50; P=0.0001) and per-vessel basis (area under the receiver operating characteristic curve, 0.79 versus 0.53; P<0.0001). FFRCT demonstrated significant reclassification of CT stenosis for lesion-specific ischemia (net reclassification improvement, 0.45; 95% confidence interval, 0.25-0.65; P=0.01). CONCLUSIONS: FFRCT possesses high diagnostic performance for diagnosis of ischemic for lesions of intermediate stenosis severity. Notably, the high sensitivity and negative predictive value suggest the ability of FFRCT to effectively rule out intermediate lesions that cause ischemia.
Authors: Amit Pursnani; Ashley M Lee; Thomas Mayrhofer; Waleed Ahmed; Shanmugam Uthamalingam; Maros Ferencik; Stefan B Puchner; Fabian Bamberg; Christopher L Schlett; James Udelson; Udo Hoffmann; Brian B Ghoshhajra Journal: Circ Cardiovasc Imaging Date: 2015-03 Impact factor: 7.792
Authors: Arthur E Stillman; Matthijs Oudkerk; David A Bluemke; Menko Jan de Boer; Jens Bremerich; Ernest V Garcia; Matthias Gutberlet; Pim van der Harst; W Gregory Hundley; Michael Jerosch-Herold; Dirkjan Kuijpers; Raymond Y Kwong; Eike Nagel; Stamatios Lerakis; John Oshinski; Jean-François Paul; Riemer H J A Slart; Vinod Thourani; Rozemarijn Vliegenthart; Bernd J Wintersperger Journal: Int J Cardiovasc Imaging Date: 2018-03-19 Impact factor: 2.357