Laust Dupont Rasmussen1, Simon Winther2, Jelmer Westra2, Christin Isaksen3, June Anita Ejlersen4, Lau Brix3, Jane Kirk5, Grazina Urbonaviciene5, Hanne Maare Søndergaard6, Osama Hammid7, Samuel Emil Schmidt8, Lars Lyhne Knudsen9, Lene Helleskov Madsen9, Lars Frost5, Steffen E Petersen10, Lars Christian Gormsen11, Evald Høj Christiansen2, Ashkan Eftekhari2, Niels Ramsing Holm2, Mette Nyegaard12, Amedeo Chiribiri13, Hans Erik Bøtker2, Morten Böttcher14. 1. Department of Cardiology, Hospital Unit West, Gl. Landevej 61, Herning, Denmark. Electronic address: lausra@rm.dk. 2. Department of Cardiology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus, Denmark. 3. Department of Radiology, Regional Hospital Central Jutland, Falkevej 1A, Silkeborg, Denmark. 4. Department of Nuclear Medicine, Hospital Unit West, Gl. Landevej 61, Herning, Denmark. 5. Department of Cardiology, Regional Hospital Central Jutland, Falkevej 1A, Silkeborg, Denmark. 6. Department of Cardiology, Regional Hospital Central Jutland, Heibergs Allé 4, Viborg, Denmark. 7. Department of Cardiology, Regional Hospital East Jutland, Skovlyvej 15, Randers, Denmark. 8. Department of Health Science and Technology, Aalborg University, Aalborg, Denmark. 9. Department of Cardiology, Hospital Unit West, Gl. Landevej 61, Herning, Denmark. 10. Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, West Smithfield, London, United Kingdom; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, United Kingdom. 11. Department of Nuclear Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus, Denmark. 12. Department of Biomedicine, Aarhus University, Aarhus, Denmark. 13. Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, United Kingdom. 14. Department of Cardiology, Hospital Unit West, Gl. Landevej 61, Herning, Denmark. Electronic address: morboett@rm.dk.
Abstract
BACKGROUND:Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), 82rubidium positron emission tomography (82Rb-PET), and CT-derived fractional flow reserve (FFRCT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82Rb-PET as reference standard. METHODS: Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI 82Rb-PET, FFRCT, ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion. DISCUSSION: The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR.
RCT Entities:
BACKGROUND: Coronary computed tomography angiography (CTA) is the preferred primary diagnostic modality when examining patients with low to intermediate pre-test probability of coronary artery disease (CAD). Only 20-30% of these have potentially obstructive CAD. Because of the relatively poor positive predictive value of coronary CTA, unnecessary invasive coronary angiographies (ICAs) are conducted with the costs and risks associated with the procedure. Hence, an optimized diagnostic CAD algorithm may reduce the numbers of ICAs not followed by revascularization. The Dan-NICAD 2 study has 3 equivalent main aims: (1) To examine the diagnostic precision of a sound-based diagnostic algorithm, The CADScor®System (Acarix A/S, Denmark), in patients with a low to intermediate pre-test risk of CAD referred to a primary examination by coronary CTA. We hypothesize that the CADScor®System provides better stratification prior to coronary CTA than clinical risk stratification scores alone. (2) To compare the diagnostic accuracy of 3T cardiac magnetic resonance imaging (3T CMRI), 82rubidium positron emission tomography (82Rb-PET), and CT-derived fractional flow reserve (FFRCT) in patients where obstructive CAD cannot be ruled out by coronary CTA using ICA fractional flow reserve (FFR) as reference standard. (3) To compare the diagnostic performance of quantitative flow ratio (QFR) and ICA-FFR in patients with low to intermediate pre-test probability of CAD using 82Rb-PET as reference standard. METHODS:Dan-NICAD 2 is a prospective, multicenter, cross-sectional study including approximately 2,000 patients with low to intermediate pre-test probability of CAD and without previous history of CAD. Patients are referred to coronary CTA because of symptoms suggestive of CAD, as evaluated by a cardiologist. Patient interviews, sound recordings, and blood samples are obtained in connection with the coronary CTA. If coronary CTA does not rule out obstructive CAD, patients will be examined by 3T CMRI 82Rb-PET, FFRCT, ICA, and FFR. Reference standard is ICA-FFR. Obstructive CAD is defined as an FFR ≤0.80 or as high-grade stenosis (>90% diameter stenosis) by visual assessment. Diagnostic performance will be evaluated as sensitivity, specificity, predictive values, likelihood ratios, calibration, and discrimination. Enrolment started January 2018 and is expected to be completed by June 2020. Patients are followed for 10 years after inclusion. DISCUSSION: The results of the Dan-NICAD 2 study are expected to contribute to the improvement of diagnostic strategies for patients suspected of CAD in 3 different steps: risk stratification prior to coronary CTA, diagnostic strategy after coronary CTA, and invasive wireless QFR analysis as an alternative to ICA-FFR.
Authors: Martin Sejr-Hansen; Jelmer Westra; Simon Winther; Shengxian Tu; Louise Nissen; Lars Gormsen; Steffen E Petersen; June Ejlersen; Christin Isaksen; Hans Erik Bøtker; Morten Bøttcher; Evald H Christiansen; Niels Ramsing Holm Journal: Int J Cardiovasc Imaging Date: 2019-11-19 Impact factor: 2.357