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Combining automated attenuation-based tube voltage selection and iterative reconstruction: a liver phantom study


Husarik, Daniela B; Schindera, Sebastian T; Morsbach, Fabian; Chuck, Natalie; Seifert, Burkhardt; Szucs-Farkas, Zsolt; Alkadhi, Hatem (2014). Combining automated attenuation-based tube voltage selection and iterative reconstruction: a liver phantom study. European Radiology, 24(3):657-667.

Abstract

OBJECTIVES: To determine the value of combined automated attenuation-based tube-potential selection and iterative reconstructions (IRs) for optimising computed tomography (CT) imaging of hypodense liver lesions.
METHODS: A liver phantom containing hypodense lesions was imaged by CT with and without automated attenuation-based tube-potential selection (80, 100 and 120 kVp). Acquisitions were reconstructed with filtered back projection (FBP) and sinogram-affirmed IR. Image noise and contrast-to-noise ratio (CNR) were measured. Two readers marked lesion localisation and rated confidence, sharpness, noise and image quality on a five-point scale (1 = worst, 5 = best).
RESULTS: Image noise was lower (31-52 %) and CNR higher (43-102 %) on IR than on FBP images at all tube voltages. On 100-kVp and 80-kVp IR images, confidence and sharpness were higher than on 120-kVp FBP images. Scores for image quality score and noise as well as sensitivity for 100-kVp IR were similar or higher than for 120-kVp FBP and lower for 80-kVp IR. Radiation dose was reduced by 26 % at 100 kVp and 56 % at 80 kVp.
CONCLUSIONS: Compared with 120-kVp FBP images, the combination of automated attenuation-based tube-potential selection at 100 kVp and IR provides higher image quality and improved sensitivity for detecting hypodense liver lesions in vitro at a dose reduced by 26 %.
KEY POINTS: • Combining automated tube voltage selection/iterative CT reconstruction improves image quality. • Attenuation values remain stable on IR compared with FBP images. • Lesion detection was highest on 100-kVp IR images.

Abstract

OBJECTIVES: To determine the value of combined automated attenuation-based tube-potential selection and iterative reconstructions (IRs) for optimising computed tomography (CT) imaging of hypodense liver lesions.
METHODS: A liver phantom containing hypodense lesions was imaged by CT with and without automated attenuation-based tube-potential selection (80, 100 and 120 kVp). Acquisitions were reconstructed with filtered back projection (FBP) and sinogram-affirmed IR. Image noise and contrast-to-noise ratio (CNR) were measured. Two readers marked lesion localisation and rated confidence, sharpness, noise and image quality on a five-point scale (1 = worst, 5 = best).
RESULTS: Image noise was lower (31-52 %) and CNR higher (43-102 %) on IR than on FBP images at all tube voltages. On 100-kVp and 80-kVp IR images, confidence and sharpness were higher than on 120-kVp FBP images. Scores for image quality score and noise as well as sensitivity for 100-kVp IR were similar or higher than for 120-kVp FBP and lower for 80-kVp IR. Radiation dose was reduced by 26 % at 100 kVp and 56 % at 80 kVp.
CONCLUSIONS: Compared with 120-kVp FBP images, the combination of automated attenuation-based tube-potential selection at 100 kVp and IR provides higher image quality and improved sensitivity for detecting hypodense liver lesions in vitro at a dose reduced by 26 %.
KEY POINTS: • Combining automated tube voltage selection/iterative CT reconstruction improves image quality. • Attenuation values remain stable on IR compared with FBP images. • Lesion detection was highest on 100-kVp IR images.

Citations

14 citations in Web of Science®
12 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Diagnostic and Interventional Radiology
04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2014
Deposited On:29 Oct 2013 15:02
Last Modified:05 Apr 2016 17:05
Publisher:Springer
ISSN:0938-7994
Publisher DOI:https://doi.org/10.1007/s00330-013-3049-x
PubMed ID:24154792

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