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Detection of ischaemicmyocardial lesions with coronary ct angiography and adenosine-stress dynamic perfusion imaging using a 128-slice dual-source ct: Diagnostic performance in comparison with cardiac mri

  • Sungkyunkwan University

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: We assessed the diagnostic performance of adenosine-stress dynamic CT perfusion (ASDCTP) imaging and coronary CT angiography (CCTA) for the detection of ischaemic myocardial lesions using 128-slice dual-source CT compared with that of 1.5 T cardiac MRI. Methods: Thisprospective study included33patients (6168 years, 82% male) with suspected coronary artery diseases who underwent ASDCTP imaging and adenosine-stress cardiac MRI. Two investigators independently evaluated ASDCTP images in correlation with significant coronary stenosis on CCTAusing two different thresholds of 50%and 70% diameter stenosis. Hypoattenuatedmyocardial lesions on ASDCTP associated with significant coronary stenoses on CCTA were regarded as true perfusion defects. All estimates of diagnostic performance were calculated and compared with those of cardiac MRI. Results: With use of a threshold of 50% diameter stenosis on CCTA, the diagnostic estimates per-myocardial segment were as follows: sensitivity, 81% [95% confidence interval (CI): 70-92%]; specificity, 94% (95% CI: 92-96%); andaccuracy 93%(95%CI: 91-95%). With useof a threshold of 70%, the diagnostic estimates were as follows: sensitivity, 48% (95% CI: 34-62%); specificity, 99% (95% CI: 98-100%); and accuracy, 94% (95% CI: 92-96%). Conclusion: Dynamic CTP using 128-slice dual-source CT enables the assessment of the physiological significance of coronary artery lesions with high diagnostic accuracy in patients with clinically suspected coronary artery disease. Advances in knowledge: Combined CCTA and ASDCTP yielded high accuracy in the detection of perfusion defects regardless of the threshold of significant coronary stenosis.

Original languageEnglish
Article number20130481
JournalBritish Journal of Radiology
Volume86
Issue number1032
DOIs
StatePublished - 1 Dec 2013

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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