Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG

Abstract Background Block-sequential regularized expectation maximization (BSREM), commercially Q. Clear (GE Healthcare, Milwaukee, WI, USA), is a reconstruction algorithm that allows for a fully convergent iterative reconstruction leading to higher image contrast compared to conventional reconstruc...

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Main Authors: Elin Trägårdh, David Minarik, Helén Almquist, Ulrika Bitzén, Sabine Garpered, Erland Hvittfelt, Berit Olsson, Jenny Oddstig
Format: Article
Language:English
Published: SpringerOpen 2019-07-01
Series:EJNMMI Research
Subjects:
FDG
Online Access:http://link.springer.com/article/10.1186/s13550-019-0535-4
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spelling doaj-3a32f399c7f24cf0a91ab78a289f25e82020-11-25T03:54:04ZengSpringerOpenEJNMMI Research2191-219X2019-07-019111010.1186/s13550-019-0535-4Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDGElin Trägårdh0David Minarik1Helén Almquist2Ulrika Bitzén3Sabine Garpered4Erland Hvittfelt5Berit Olsson6Jenny Oddstig7Clinical Physiology and Nuclear Medicine, Skåne University HospitalRadiation Physics, Skåne University HospitalClinical Physiology and Nuclear Medicine, Skåne University HospitalClinical Physiology and Nuclear Medicine, Skåne University HospitalClinical Physiology and Nuclear Medicine, Skåne University HospitalClinical Physiology and Nuclear Medicine, Skåne University HospitalClinical Physiology and Nuclear Medicine, Skåne University HospitalRadiation Physics, Skåne University HospitalAbstract Background Block-sequential regularized expectation maximization (BSREM), commercially Q. Clear (GE Healthcare, Milwaukee, WI, USA), is a reconstruction algorithm that allows for a fully convergent iterative reconstruction leading to higher image contrast compared to conventional reconstruction algorithms, while also limiting noise. The noise penalization factor β controls the trade-off between noise level and resolution and can be adjusted by the user. The aim was to evaluate the influence of different β values for different activity time products (ATs = administered activity × acquisition time) in whole-body 18F-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) regarding quantitative data, interpretation, and quality assessment of the images. Twenty-five patients with known or suspected malignancies, referred for clinical 18F-FDG PET-CT examinations acquired on a silicon photomultiplier PET-CT scanner, were included. The data were reconstructed using BSREM with β values of 100–700 and ATs of 4–16 MBq/kg × min/bed (acquisition times of 1, 1.5, 2, 3, and 4 min/bed). Noise level, lesion SUVmax, and lesion SUVpeak were calculated. Image quality and lesion detectability were assessed by four nuclear medicine physicians for acquisition times of 1.0 and 1.5 min/bed position. Results The noise level decreased with increasing β values and ATs. Lesion SUVmax varied considerably between different β values and ATs, whereas SUVpeak was more stable. For an AT of 6 (in our case 1.5 min/bed), the best image quality was obtained with a β of 600 and the best lesion detectability with a β of 500. AT of 4 generated poor-quality images and false positive uptakes due to noise. Conclusions For oncologic whole-body 18F-FDG examinations on a SiPM-based PET-CT, we propose using an AT of 6 (i.e., 4 MBq/kg and 1.5 min/bed) reconstructed with BSREM using a β value of 500–600 in order to ensure image quality and lesion detection rate as well as a high patient throughput. We do not recommend using AT < 6 since the risk of false positive uptakes due to noise increases.http://link.springer.com/article/10.1186/s13550-019-0535-4PET-CTFDGImage reconstructionQ. ClearBlock-sequential regularized expectation maximization
collection DOAJ
language English
format Article
sources DOAJ
author Elin Trägårdh
David Minarik
Helén Almquist
Ulrika Bitzén
Sabine Garpered
Erland Hvittfelt
Berit Olsson
Jenny Oddstig
spellingShingle Elin Trägårdh
David Minarik
Helén Almquist
Ulrika Bitzén
Sabine Garpered
Erland Hvittfelt
Berit Olsson
Jenny Oddstig
Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
EJNMMI Research
PET-CT
FDG
Image reconstruction
Q. Clear
Block-sequential regularized expectation maximization
author_facet Elin Trägårdh
David Minarik
Helén Almquist
Ulrika Bitzén
Sabine Garpered
Erland Hvittfelt
Berit Olsson
Jenny Oddstig
author_sort Elin Trägårdh
title Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
title_short Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
title_full Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
title_fullStr Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
title_full_unstemmed Impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a Si-photomultiplier-based PET-CT system for 18F-FDG
title_sort impact of acquisition time and penalizing factor in a block-sequential regularized expectation maximization reconstruction algorithm on a si-photomultiplier-based pet-ct system for 18f-fdg
publisher SpringerOpen
series EJNMMI Research
issn 2191-219X
publishDate 2019-07-01
description Abstract Background Block-sequential regularized expectation maximization (BSREM), commercially Q. Clear (GE Healthcare, Milwaukee, WI, USA), is a reconstruction algorithm that allows for a fully convergent iterative reconstruction leading to higher image contrast compared to conventional reconstruction algorithms, while also limiting noise. The noise penalization factor β controls the trade-off between noise level and resolution and can be adjusted by the user. The aim was to evaluate the influence of different β values for different activity time products (ATs = administered activity × acquisition time) in whole-body 18F-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) regarding quantitative data, interpretation, and quality assessment of the images. Twenty-five patients with known or suspected malignancies, referred for clinical 18F-FDG PET-CT examinations acquired on a silicon photomultiplier PET-CT scanner, were included. The data were reconstructed using BSREM with β values of 100–700 and ATs of 4–16 MBq/kg × min/bed (acquisition times of 1, 1.5, 2, 3, and 4 min/bed). Noise level, lesion SUVmax, and lesion SUVpeak were calculated. Image quality and lesion detectability were assessed by four nuclear medicine physicians for acquisition times of 1.0 and 1.5 min/bed position. Results The noise level decreased with increasing β values and ATs. Lesion SUVmax varied considerably between different β values and ATs, whereas SUVpeak was more stable. For an AT of 6 (in our case 1.5 min/bed), the best image quality was obtained with a β of 600 and the best lesion detectability with a β of 500. AT of 4 generated poor-quality images and false positive uptakes due to noise. Conclusions For oncologic whole-body 18F-FDG examinations on a SiPM-based PET-CT, we propose using an AT of 6 (i.e., 4 MBq/kg and 1.5 min/bed) reconstructed with BSREM using a β value of 500–600 in order to ensure image quality and lesion detection rate as well as a high patient throughput. We do not recommend using AT < 6 since the risk of false positive uptakes due to noise increases.
topic PET-CT
FDG
Image reconstruction
Q. Clear
Block-sequential regularized expectation maximization
url http://link.springer.com/article/10.1186/s13550-019-0535-4
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