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Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors

Overview of attention for article published in EJNMMI Physics, September 2018
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Title
Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors
Published in
EJNMMI Physics, September 2018
DOI 10.1186/s40658-018-0223-x
Pubmed ID
Authors

Michael Messerli, Paul Stolzmann, Michèle Egger-Sigg, Josephine Trinckauf, Stefano D’Aguanno, Irene A. Burger, Gustav K. von Schulthess, Philipp A. Kaufmann, Martin W. Huellner

Abstract

The aim of this study was to evaluate and compare PET image reconstruction algorithms on novel digital silicon photomultiplier PET/CT in patients with newly diagnosed and histopathologically confirmed lung cancer. A total of 45 patients undergoing 18F-FDG PET/CT for initial lung cancer staging were included. PET images were reconstructed using ordered subset expectation maximization (OSEM) with time-of-flight and point spread function modelling as well as Bayesian penalized likelihood reconstruction algorithm (BSREM) with different β-values yielding a total of 7 datasets per patient. Subjective and objective image assessment with all image datasets was carried out, including subgroup analyses for patients with high dose (> 2.0 MBq/kg) and low dose (≤ 2.0 MBq/kg) of 18F-FDG injection regimen. Subjective image quality ratings were significantly different among all different reconstruction algorithms as well as among BSREM using different β-values only (both p < 0.001). BSREM with a β-value of 600 was assigned the highest score for general image quality, image sharpness, and lesion conspicuity. BSREM reconstructions resulted in higher SUVmax of lung tumors compared to OSEM of up to + 28.0% (p < 0.001). BSREM reconstruction resulted in higher signal-/ and contrast-to-background ratios of lung tumor and higher signal-/ and contrast-to-noise ratio compared to OSEM up to a β-value of 800. Lower β-values (BSREM450) resulted in the best image quality for high dose 18F-FDG injections, whereas higher β-values (BSREM600) lead to the best image quality in low dose 18F-FDG PET/CT (p < 0.05). BSREM reconstruction algorithm used in digital detector PET leads to significant increases of lung tumor SUVmax, signal-to-background ratio, and signal-to-noise ratio, which translates into a higher image quality, tumor conspicuity, and image sharpness.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 16%
Student > Master 4 11%
Other 3 8%
Professor > Associate Professor 3 8%
Student > Ph. D. Student 3 8%
Other 4 11%
Unknown 14 38%
Readers by discipline Count As %
Medicine and Dentistry 8 22%
Physics and Astronomy 7 19%
Engineering 4 11%
Nursing and Health Professions 1 3%
Mathematics 1 3%
Other 2 5%
Unknown 14 38%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 September 2018.
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#12,028,061
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Outputs from EJNMMI Physics
#48
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#228,609
of 265,180 outputs
Outputs of similar age from EJNMMI Physics
#1
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