Adriaan Coenen1, Alexia Rossi2, Marisa M Lubbers3, Akira Kurata4, Atsushi K Kono4, Raluca G Chelu4, Sabrina Segreto5, Marcel L Dijkshoorn4, Andrew Wragg5, Robert-Jan M van Geuns3, Francesca Pugliese5, Koen Nieman3. 1. Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands. Electronic address: a.coenen@erasmusmc.nl. 2. Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Centre for Advanced Cardiovascular Imaging, NIHR Cardiovascular Biomedical Research Unit at Barts, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London & St. Bartholomew's Hospital, London, United Kingdom. 3. Department of Cardiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands. 4. Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands. 5. Centre for Advanced Cardiovascular Imaging, NIHR Cardiovascular Biomedical Research Unit at Barts, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London & St. Bartholomew's Hospital, London, United Kingdom.
Abstract
OBJECTIVES: The aim of this study was to investigate the individual and combined accuracy of dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed tomography angiography (CTA) fractional flow reserve (FFR) for the identification of functionally relevant coronary artery disease (CAD). BACKGROUND: Coronary CTA has become an established diagnostic test for ruling out CAD, but it does not allow interpretation of the hemodynamic severity of stenotic lesions. Two recently introduced functional CT techniques are dynamic MPI and CTA FFR using computational fluid dynamics. METHODS: From 2 institutions, 74 patients (n = 62 men, mean age 61 years) planned for invasive angiography with invasive FFR measurement in 142 vessels underwent CTA imaging and dynamic CT MPI during adenosine vasodilation. A patient-specific myocardial blood flow index was calculated, normalized to remote myocardial global left ventricular blood flow. CTA FFR was computed using an on-site, clinician-operated application. Using binary regression, a single functional CT variable was created combining both CT MPI and CTA FFR. Finally, stepwise diagnostic work-up of CTA FFR with selective use of CT MPI was simulated. The diagnostic performance of CT MPI, CTA FFR, and CT MPI integrated with CTA FFR was evaluated using C statistics with invasive FFR, with a threshold of 0.80 as a reference. RESULTS: Sensitivity, specificity, and accuracy were 73% (95% confidence interval [CI]: 61% to 86%), 68% (95% CI: 56% to 80%), and 70% (95% CI: 62% to 79%) for CT MPI and 82% (95% CI: 72% to 92%), 60% (95% CI: 48% to 72%), and 70% (63% to 80%) for CTA FFR. For CT MPI integrated with CTA FFR, diagnostic accuracy was 79% (95% CI: 71% to 87%), with improvement of the area under the curve from 0.78 to 0.85 (p < 0.05). Accuracy of the stepwise approach was 77%. CONCLUSIONS: CT MPI and CTA FFR both identify functionally significant CAD, with comparable accuracy. Diagnostic performance can be improved by combining the techniques. A stepwise approach, reserving CT MPI for intermediate CTA FFR results, also improves diagnostic performance while omitting nearly one-half of the population from CT MPI examinations.
OBJECTIVES: The aim of this study was to investigate the individual and combined accuracy of dynamic computed tomography (CT) myocardial perfusion imaging (MPI) and computed tomography angiography (CTA) fractional flow reserve (FFR) for the identification of functionally relevant coronary artery disease (CAD). BACKGROUND: Coronary CTA has become an established diagnostic test for ruling out CAD, but it does not allow interpretation of the hemodynamic severity of stenotic lesions. Two recently introduced functional CT techniques are dynamic MPI and CTA FFR using computational fluid dynamics. METHODS: From 2 institutions, 74 patients (n = 62 men, mean age 61 years) planned for invasive angiography with invasive FFR measurement in 142 vessels underwent CTA imaging and dynamic CT MPI during adenosine vasodilation. A patient-specific myocardial blood flow index was calculated, normalized to remote myocardial global left ventricular blood flow. CTA FFR was computed using an on-site, clinician-operated application. Using binary regression, a single functional CT variable was created combining both CT MPI and CTA FFR. Finally, stepwise diagnostic work-up of CTA FFR with selective use of CT MPI was simulated. The diagnostic performance of CT MPI, CTA FFR, and CT MPI integrated with CTA FFR was evaluated using C statistics with invasive FFR, with a threshold of 0.80 as a reference. RESULTS: Sensitivity, specificity, and accuracy were 73% (95% confidence interval [CI]: 61% to 86%), 68% (95% CI: 56% to 80%), and 70% (95% CI: 62% to 79%) for CT MPI and 82% (95% CI: 72% to 92%), 60% (95% CI: 48% to 72%), and 70% (63% to 80%) for CTA FFR. For CT MPI integrated with CTA FFR, diagnostic accuracy was 79% (95% CI: 71% to 87%), with improvement of the area under the curve from 0.78 to 0.85 (p < 0.05). Accuracy of the stepwise approach was 77%. CONCLUSIONS: CT MPI and CTA FFR both identify functionally significant CAD, with comparable accuracy. Diagnostic performance can be improved by combining the techniques. A stepwise approach, reserving CT MPI for intermediate CTA FFR results, also improves diagnostic performance while omitting nearly one-half of the population from CT MPI examinations.
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