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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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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