OBJECTIVES: A proof-of-concept study was undertaken to determine whether differences in corrected coronary opacification (CCO) within coronary lumen can identify arteries with abnormal resting coronary flow. BACKGROUND: Although computed tomographic coronary angiography can be used for the detection of obstructive coronary artery disease, it cannot reliably differentiate between anatomical and functional stenoses. METHODS: Computed tomographic coronary angiography patients (without history of revascularization, cardiac transplantation, and congenital heart disease) who underwent invasive coronary angiography were enrolled. Attenuation values of coronary lumen were measured before and after stenoses and normalized to the aorta. Changes in CCO were calculated, and CCO differences were compared with severity of coronary stenosis and Thrombolysis In Myocardial Infarction (TIMI) flow at the time of invasive coronary angiography. RESULTS: One hundred four coronary arteries (n = 52, mean age = 60.0 ± 9.5 years; men = 71.2%) were assessed. Compared with normal arteries, the CCO differences were greater in arteries with computed tomographic coronary angiography diameter stenoses ≥ 50%. Similarly, CCO differences were greater in arteries with TIMI flow grade < 3 (0.406 ± 0.226) compared with those with normal flow (TIMI flow grade 3) (0.078 ± 0.078, p < 0.001). With CCO differences, abnormal coronary flow (TIMI flow grade < 3) was identified with a sensitivity and specificity, positive predictive value, and negative predictive value of 83.3% (95% confidence interval [CI]: 57.7 to 95.6%), 91.2% (95% CI: 75.2% to 97.7%), 83.3% (95% CI: 57.7% to 95.6%), and 91.2% (95% CI: 75.2% to 97.7%), respectively. Accuracy of this method was 88.5% with very good agreement (kappa = 0.75, 95% CI: 0.55 to 0.94). CONCLUSIONS: Changes in CCO across coronary stenoses seem to predict abnormal (TIMI flow grade < 3) resting coronary blood flow. Further studies are needed to understand its incremental diagnostic value and its potential to measure stress coronary blood flow.
OBJECTIVES: A proof-of-concept study was undertaken to determine whether differences in corrected coronary opacification (CCO) within coronary lumen can identify arteries with abnormal resting coronary flow. BACKGROUND: Although computed tomographic coronary angiography can be used for the detection of obstructive coronary artery disease, it cannot reliably differentiate between anatomical and functional stenoses. METHODS: Computed tomographic coronary angiography patients (without history of revascularization, cardiac transplantation, and congenital heart disease) who underwent invasive coronary angiography were enrolled. Attenuation values of coronary lumen were measured before and after stenoses and normalized to the aorta. Changes in CCO were calculated, and CCO differences were compared with severity of coronary stenosis and Thrombolysis In Myocardial Infarction (TIMI) flow at the time of invasive coronary angiography. RESULTS: One hundred four coronary arteries (n = 52, mean age = 60.0 ± 9.5 years; men = 71.2%) were assessed. Compared with normal arteries, the CCO differences were greater in arteries with computed tomographic coronary angiography diameter stenoses ≥ 50%. Similarly, CCO differences were greater in arteries with TIMI flow grade < 3 (0.406 ± 0.226) compared with those with normal flow (TIMI flow grade 3) (0.078 ± 0.078, p < 0.001). With CCO differences, abnormal coronary flow (TIMI flow grade < 3) was identified with a sensitivity and specificity, positive predictive value, and negative predictive value of 83.3% (95% confidence interval [CI]: 57.7 to 95.6%), 91.2% (95% CI: 75.2% to 97.7%), 83.3% (95% CI: 57.7% to 95.6%), and 91.2% (95% CI: 75.2% to 97.7%), respectively. Accuracy of this method was 88.5% with very good agreement (kappa = 0.75, 95% CI: 0.55 to 0.94). CONCLUSIONS: Changes in CCO across coronary stenoses seem to predict abnormal (TIMI flow grade < 3) resting coronary blood flow. Further studies are needed to understand its incremental diagnostic value and its potential to measure stress coronary blood flow.
Authors: Rine Nakanishi; Suguru Matsumoto; Anas Alani; Dong Li; Pieter H Kitslaar; Alexander Broersen; Bon-Kwon Koo; James K Min; Matthew J Budoff Journal: Int J Cardiovasc Imaging Date: 2015-04-24 Impact factor: 2.357
Authors: Noelia Grande Gutierrez; Olga Shirinsky; Nina Gagarina; Galina Lyskina; Ryuji Fukazawa; Shunichi Ogawa; Jane C Burns; Alison L Marsden; Andrew M Kahn Journal: Am J Cardiol Date: 2017-05-30 Impact factor: 2.778
Authors: Wynand J Stuijfzand; Ibrahim Danad; Pieter G Raijmakers; C Bogdan Marcu; Martijn W Heymans; Cornelis C van Kuijk; Albert C van Rossum; Koen Nieman; James K Min; Jonathon Leipsic; Niels van Royen; Paul Knaapen Journal: JACC Cardiovasc Imaging Date: 2014-03-13
Authors: Brian S Ko; Sujith Seneviratne; James D Cameron; Sarah Gutman; Marcus Crossett; Kiran Munnur; Ian T Meredith; Dennis T L Wong Journal: Int J Cardiovasc Imaging Date: 2016-03-07 Impact factor: 2.357