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Proceedings Paper

A multireader diagnostic performance study of low-contrast detectability on a third-generation dual-source CT scanner: filtered back projection versus advanced modeled iterative reconstruction
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Paper Abstract

The purpose of this work was to compare CT low-contrast detectability between two reconstruction algorithms, filtered back-projection (FBP) and advanced modeled iterative reconstruction (ADMIRE). A phantom was designed with a range of low-contrast circular inserts representing 5 contrast levels and 3 sizes. The phantom was imaged on a third-generation dual-source CT scanner (SOMATOM Definition Force, Siemens Healthcare) under various dose levels (0.74 – 5.8 mGy CTDIVol). Images were reconstructed using different settings of slice thickness (0.6 – 5 mm) and reconstruction algorithms (FBP and ADMIRE with strength of 3-5) and were assessed by eleven blinded and independent readers using a two alternative forced choice (2AFC) detection experiment. A second observer experiment was further performed in which observers scored the images based on the total number of visible object groups. Detection performance increased with increasing contrast, size, dose, with accuracy ranging from 50% (i.e., guessing) to 87% with an average inter-observer variability of ±7%. The use of ADMIRE-3 increased performance by 5.2% resulting in an estimated dose reduction potential of 56-60%. The results from the second experiment also showed increased number of visible object groups for increasing dose, slice thickness, and ADMIRE strength. The score difference between FBP and ADMIRE was 0.9, 1.3, and 2.1 for ADMIRE strengths of 3, 4, and 5, respectively, resulting in estimated dose reduction potentials between 4-80%. Overall, the data indicated potential to image at reduced doses while maintaining comparable image quality when using ADMIRE compared to FBP.

Paper Details

Date Published: 17 March 2015
PDF: 8 pages
Proc. SPIE 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, 94160D (17 March 2015); doi: 10.1117/12.2081647
Show Author Affiliations
Justin Solomon, Duke Univ. Medical Ctr. (United States)
Duke Univ. (United States)
Achille Mileto, Duke Univ. Medical Ctr. (United States)
Juan Carlos Ramirez-Giraldo, Siemens Medical Solutions USA, Inc. (United States)
Ehsan Samei, Duke Univ. Medical Ctr. (United States)
Duke Univ. (United States)

Published in SPIE Proceedings Vol. 9416:
Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment
Claudia R. Mello-Thoms; Matthew A. Kupinski, Editor(s)

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