Dual-energy computed tomography (DECT) has been proposed for the comprehensive assessment of coronary artery stenosis and myocardial perfusion yet traditionally required reducing the temporal resolution of cardiac studies. We evaluated a reconstruction algorithm that preserves high temporal resolution at cardiac DECT.
Twelve consecutive patients (3 women; mean [SD] age, 64  years) with an abnormal single photon emission CT result underwent invasive coronary angiography and cardiac DECT. Dual-energy CT studies were reconstructed using the standard algorithm with 165-millisecond temporal resolution and a hybrid algorithm providing 83-millisecond temporal resolution. These studies were rated for coronary image quality and motion artifacts and compared with invasive coronary angiographic studies.
One hundred sixty-eight coronary artery segments (82%) were evaluated. The standard 165-millisecond reconstruction provided 95% diagnostic segments compared with 100% using the 83-millisecond hybrid reconstruction. Image quality was rated significantly (P < 0.05) better with hybrid reconstruction and had 91.4% sensitivity, 94.7% specificity, 82.1% positive predictive value, and 97.7% negative predictive value for detecting significant stenosis versus 85.7%, 93.2%, 76.9%, and 96.1% with standard reconstruction, respectively.
Hybrid image reconstruction mitigates the former limitations in temporal resolution of cardiac DECT.
From the *Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC; †Department of Radiology, University of Navarra, Pamplona, Spain; ‡Department of Radiology, Ajou University Hospital, Suwon, South Korea; §Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC; and ∥Division Computed Tomography, Siemens Medical Solutions, Forchheim, Germany.
Received for publication June 7, 2010; accepted August 17, 2010.
Reprints: John W. Nance Jr, MD, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, MSC 226, Charleston, SC 29401 (e-mail: NANCEJ@MUSC.EDU).
SV, BS, RR, and TGF are employees of Siemens Medical Solutions. UJS is a consultant for and receives research support from Bayer-Schering, Bracco, General Electric, Medrad, and Siemens. GB is a consultant for General Electric, Medrad, and Siemens. The other authors have no conflict of interest to disclose.