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Comparative Study
. 2016 Nov;43(11):5925.
doi: 10.1118/1.4962651.

Energy subtraction angiography is comparable to digital subtraction angiography in terms of iodine Rose SNR

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Comparative Study

Energy subtraction angiography is comparable to digital subtraction angiography in terms of iodine Rose SNR

Christiane S Burton et al. Med Phys. 2016 Nov.

Abstract

Purpose: X-ray digital subtraction angiography (DSA) is widely used for vascular imaging. However, motion artifacts render it largely unsuccessful for some applications including cardiac imaging. Dual-energy imaging using fast kV switching was proposed in the past to provide the benefits of DSA with fewer motion artifacts, but image quality was inferior to DSA. This study compares the iodine Rose SNR that can be achieved using dual-energy methods, called energy-subtraction angiography (ESA), with that of DSA and examines the technical conditions required to achieve near-optimal SNR.

Methods: A Rose SNR model is described, experimentally validated, and used to compare ESA with DSA. The model considers detector quantum efficiency, readout noise (quantum-limit exposure), and scatter-to-primary ratio.

Results: The theoretical Rose SNR showed excellent agreement with experimental results for both ESA and DSA images, and shows that near-optimal SNR is harder to achieve with ESA than DSA. In comparison to DSA, ESA requires: (1) high detector quantum efficiency at a higher energy (120 kV); (2) lower detector readout noise by a factor of four (approximately 0.005 μGy air KERMA or lower); and (3) lower scatter-to-primary ratio by a factor of three (approximately 0.05 or lower). These conditions were not achievable in the past, and remain difficult but not impossible to achieve at present.

Conclusions: ESA and DSA can provide similar iodine Rose SNR for the same patient exposure, but only when satisfying the above conditions. This may explain why dual-energy methods have been unsuccessful in the past and suggests ESA methods may offer a viable alternative to DSA when implemented under optimal conditions.

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