Rationale and Objectives
We sought to explore the image quality and diagnostic performance of virtual monochromatic imaging derived from dual-energy computed tomography coronary angiography (DE-CTCA) in patients with intermediate to high likelihood of coronary artery disease (CAD) and the influence of calcification.
Materials and Methods
Consecutive symptomatic patients with suspected CAD referred for invasive coronary angiography who underwent DE-CTCA and a coronary artery calcium scoring before the invasive procedure comprised the study population.
Results
Sixty-seven patients were included. Image quality was significantly lower at 45 keV reconstructions (mean Likert score 45 keV 3.57 ± 0.6, 65 keV 4.07 ± 0.5, and 85 keV 4.09 ± 0.6; P < .0001). Patients with moderate calcification showed a trend toward a significant improvement in the diagnostic performance with 65 keV vs 45 keV reconstructions (45 keV, area under the curve 0.92 [95% confidence interval 0.89–0.95] vs 65 keV, area under the curve 0.96 [95% confidence interval 0.93–0.98], P = .06). The diagnostic performance of DE-CTCA was significantly lower in segments with higher coronary artery calcium scoring compared to segments with none or mild calcification, independent of the energy level applied.
Conclusions
In patients with intermediate to high likelihood of CAD, DE-CTCA had a good diagnostic performance, although significantly lower in segments with severe calcification.
Introduction
Computed tomography coronary angiography (CTCA) has been established as a valuable noninvasive diagnostic tool for the assessment of symptomatic patients with low to intermediate likelihood of coronary artery disease (CAD) . Notwithstanding, patients with intermediate to high likelihood of CAD have been consistently excluded from clinical studies involving this technology and consequently from diagnostic algorithms. To some extent, this has been attributed to the intricate distinction between heavily calcified plaques and luminal opacification that hamper the precise quantification of coronary stenosis . Calcified plaques usually seem larger on conventional single-energy computed tomography due to a number of technical issues such as blooming, beam hardening, and partial-volume effects, frequently leading to false-positive findings and therefore to potential unnecessary referral to invasive angiography .
Virtual monochromatic imaging derived from dual-energy computed tomography coronary angiography (DE-CTCA) shows promise to attenuate some of the aforementioned limitations and therefore might provide a more accurate assessment of high-risk patients . Briefly, the basic principle of DE-CTCA is the acquisition of two datasets from the same anatomic location with different kVp, which allows for synthesized monochromatic image reconstructions at different energy levels ranging from 40 to 140 keV. Although at the expense of higher image noise and blooming, lower energy levels yield higher intraluminal enhancement that allows a substantial iodine volume load reduction . In contrast, higher energy levels not only render a reduction in image noise and blooming but are also associated with significant reduction in luminal attenuation. We therefore sought to evaluate the image quality and diagnostic performance of DE-CTCA and the influence of different energy levels and extent of coronary calcification to accurately detect coronary stenosis in patients with intermediate to high likelihood of CAD.
Methods
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Image Acquisition
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Image Analysis
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Statistical Analysis
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Results
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Table 1
Demographical Characteristics ( n = 67)
N (%) Age (years ± SD) 61.3 ± 11.1 Male (%) 51(70%) Body mass index (kg/m 2 ) 28.3 ± 3.4 Diabetes (%) 14(21%) Hypertension (%) 47(70%) Hypercholesterolemia (%) 45(67%) Smoking (%) 38(57%) Previous myocardial infarction (%) 16(23%) Left ventricular ejection fraction (% ± SD) 57.3 ± 13.4 Systolic blood pressure (mmHg ± SD) 141.8 ± 21.8 Diastolic blood pressure (mmHg ± SD) 86.7 ± 13.0 Heart rate (bpm ± SD) 63.4 ± 8.3 Agatston calcium score (median, IQR) 597(184–1095)
bpm, beats per minute; IQR, interquartile range; SD, standard deviation.
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Discussion
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Conclusions
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