Aims To evaluate the diagnostic power of integrating the results of computed tomography angiography (CTA) and CT myocardial perfusion (CTP) to identify coronary artery disease (CAD) defined as a flow limiting coronary artery stenosis causing a perfusion defect by single photon emission computed tomography (SPECT). Methods and results We conducted a multicentre study to evaluate the accuracy of integrated CTA-CTP for the identification of patients with flow-limiting CAD defined by ≥50% stenosis by invasive coronary angiography (ICA) with a corresponding perfusion deficit on stress single photon emission computed tomography (SPECT/MPI). Sixteen centres enroled 381 patients who underwent combined CTA-CTP and SPECT/MPI prior to conventional coronary angiography. All four image modalities were analysed in blinded independent core laboratories. The prevalence of obstructive CAD defined by combined ICA-SPECT/MPI and ICA alone was 38 and 59%, respectively. The patient-based diagnostic accuracy defined by the area under the receiver operating characteristic curve (AUC) of integrated CTA-CTP for detecting or excluding flow-limiting CAD was 0.87 [95% confidence interval (CI): 0.84-0.91]. In patients without prior myocardial infarction, the AUC was 0.90 (95% CI: 0.87-0.94) and in patients without prior CAD the AUC for combined CTA-CTP was 0.93 (95% CI: 0.89-0.97). For the combination of a CTA stenosis ≥50% stenosis and a CTP perfusion deficit, the sensitivity, specificity, positive predictive, and negative predicative values (95% CI) were 80% (72-86), 74% (68-80), 65% (58-72), and 86% (80-90), respectively. For flow-limiting disease defined by ICA-SPECT/MPI, the accuracy of CTA was significantly increased by the addition of CTP at both the patient and vessel levels. Conclusions The combination of CTA and perfusion correctly identifies patients with flow limiting CAD defined as ≥50 stenosis by ICA causing a perfusion defect by SPECT/MPI.
- Multislice computed tomography
ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine