Literature DB >> 24553783

Assessment of dose exposure and image quality in coronary angiography performed by 640-slice CT: a comparison between adaptive iterative and filtered back-projection algorithm by propensity analysis.

Ernesto Di Cesare1, Antonio Gennarelli, Alessandra Di Sibio, Valentina Felli, Alessandra Splendiani, Giovanni Luca Gravina, Antonio Barile, Carlo Masciocchi.   

Abstract

PURPOSE: This study was performed to confirm, by propensity score matching, whether the use of adaptive-iterative dose reduction (AIDR 3D) with a built-in automatic exposure control system provides clinical and dosimetric advantages with respect to the traditional filtered back-projection (FBP) algorithm without automatic exposure modulation.
MATERIALS AND METHODS: A total of 200 consecutive patients undergoing coronary computed tomography (CT) angiography on a 640-slice CT scanner were studied. A protocol with exposure parameters based on patient body mass index (BMI) and with images reconstructed using FBP (group A) was compared with a protocol with images acquired using tube current decided by an automatic exposure control system and reconstructed using AIDR (group B). Mean effective dose and image quality with both objective and subjective measurements were assessed.
RESULTS: Mean effective dose was 23.6 % lower in group B than in group A (2.56 versus 3.34 mSv; p < 0.0001). Noise was significantly lower in group B with consequent higher signal-to-noise (SNR) and contrast-to-noise (CNR) (p < 0.0001) compared with group A. Subjective quality parameters were also significantly higher in group B.
CONCLUSIONS: Comparative analysis by propensity score matching confirms that AIDR 3D with automatic exposure control is able to reduce significantly the mean radiation dose and improve the image quality compared with traditional FBP without exposure modulation.

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Year:  2014        PMID: 24553783     DOI: 10.1007/s11547-014-0382-3

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


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