Patient-specific predictors of image noise in coronary CT angiography
Schuhbaeck A, Schäfer M, Marwan M, Gauss S, Muschiol G, Lell M, Pflederer T, Ropers D, Rixe J, Hamm C, Daniel WG, Achenbach S (2013)
Publication Type: Journal article
Publication year: 2013
Journal
Book Volume: 7
Pages Range: 39-45
Journal Issue: 1
DOI: 10.1016/j.jcct.2012.10.011
Abstract
Background: Coronary computed tomography (CT) angiography can be associated with high radiation exposure. Reduction of tube voltage from 120 kV to 100 kV can reduce the dose by up to 40%, but it also increases image noise. Objective: We aimed to find a patient-specific predictor of image noise to determine the use of reduced tube voltage. Methods: Contrast-enhanced coronary dual-source CT angiography data sets [prospectively electrocardiogram (ECG)-triggered axial and retrospectively ECG-gated spiral acquisition, rotation of 280 milliseconds, 2 × 128 × 0.6 mm collimation, 100 kV, 320 mAs] of 165 patients (age, 54 ± 13 years) for the detection of coronary artery stenoses were analyzed. Image noise was measured in the aortic root. Influence of body weight, height, body mass index, thoracic cross sectional area, as well as the area of the thoracic solid tissue were analyzed. Results: Mean image noise in the aorta was 35.1 ± 8.9 HU. Mean dose length product was 207 ± 184 cm · cGy with an average effective dose of 2.9 ± 2.6 mSv. The patient cohort was divided into tertiles according to image noise. Numerous parameters, including BMI and body weight, were significantly different between the highest and lowest tertiles. In multivariable regression analysis, the area of the thoracic solid tissue was the only independent predictor of image noise (P < 0.0001). Conclusions: The area of the thoracic solid tissue at the level of the aortic root predicts image noise and may hence be used for the decision to reduce tube voltage from 120 kV to 100 kV. © 2013 Society of Cardiovascular Computed Tomography.
Authors with CRIS profile
Marcella Schäfer
Medizinische Fakultät
Mohamed Marwan
Department of Medicine 2 – Cardiology and Angiology
Michael Lell
Medizinische Fakultät
Dieter Ropers
Medizinische Fakultät
Involved external institutions
Germany (DE)How to cite
APA:
Schuhbaeck, A., Schäfer, M., Marwan, M., Gauss, S., Muschiol, G., Lell, M.,... Achenbach, S. (2013). Patient-specific predictors of image noise in coronary CT angiography. Journal of Cardiovascular Computed Tomography, 7(1), 39-45. https://doi.org/10.1016/j.jcct.2012.10.011
MLA:
Schuhbaeck, Annika, et al. "Patient-specific predictors of image noise in coronary CT angiography." Journal of Cardiovascular Computed Tomography 7.1 (2013): 39-45.
BibTeX: Download