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BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients

The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed s...

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Autores principales: Liberini, Virginia, Pizzuto, Daniele A., Messerli, Michael, Orita, Erika, Grünig, Hannes, Maurer, Alexander, Mader, Cäcilia, Husmann, Lars, Deandreis, Désirée, Kotasidis, Fotis, Trinckauf, Josey, Curioni, Alessandra, Opitz, Isabelle, Winklhofer, Sebastian, Huellner, Martin W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9156589/
https://www.ncbi.nlm.nih.gov/pubmed/35212859
http://dx.doi.org/10.1007/s10278-021-00570-y
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author Liberini, Virginia
Pizzuto, Daniele A.
Messerli, Michael
Orita, Erika
Grünig, Hannes
Maurer, Alexander
Mader, Cäcilia
Husmann, Lars
Deandreis, Désirée
Kotasidis, Fotis
Trinckauf, Josey
Curioni, Alessandra
Opitz, Isabelle
Winklhofer, Sebastian
Huellner, Martin W.
author_facet Liberini, Virginia
Pizzuto, Daniele A.
Messerli, Michael
Orita, Erika
Grünig, Hannes
Maurer, Alexander
Mader, Cäcilia
Husmann, Lars
Deandreis, Désirée
Kotasidis, Fotis
Trinckauf, Josey
Curioni, Alessandra
Opitz, Isabelle
Winklhofer, Sebastian
Huellner, Martin W.
author_sort Liberini, Virginia
collection PubMed
description The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed staging/restaging 18F-FDG PET/CT scans of 40 consecutive lung cancer patients with new brain metastases, confirmed by MRI. PET images were reconstructed using BSREM (β-values of 100, 200, 300, 400, 500, 600, 700) and OSEM. Two independent blinded readers (R1 and R2) evaluated each reconstruction using a 4-point scale for general image quality, noise, and lesion detectability. SUVmax of metastases, brain background, target-to-background ratio (TBR), and contrast recovery (CR) ratio were recorded for each reconstruction. Among all reconstruction techniques, differences in qualitative parameters were analyzed using non-parametric Friedman test, while differences in quantitative parameters were compared using analysis of variances for repeated measures. Cohen’s kappa (k) was used to measure inter-reader agreement. The overall detectability of brain metastases was highest for BSREM200 (R1: 2.83 ± 1.17; R2: 2.68 ± 1.32) and BSREM300 (R1: 2.78 ± 1.23; R2: 2.68 ± 1.36), followed by BSREM100, which had lower accuracy owing to noise. The highest median TBR was found for BSREM100 (R1: 2.19 ± 1.05; R2: 2.42 ± 1.08), followed by BSREM200 and BSREM300. Image quality ratings were significantly different among reconstructions (p < 0.001). The median quality score was higher for BSREM100-300, and both noise and metastases’ SUVmax decreased with increasing β-value. Inter-reader agreement was particularly high for the detectability of photopenic metastases and blurring (all k > 0.65). BSREM200 and BSREM300 yielded the best results for the detection of brain metastases, surpassing both BSREM400 and OSEM, typically used in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10278-021-00570-y.
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spelling pubmed-91565892022-06-02 BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients Liberini, Virginia Pizzuto, Daniele A. Messerli, Michael Orita, Erika Grünig, Hannes Maurer, Alexander Mader, Cäcilia Husmann, Lars Deandreis, Désirée Kotasidis, Fotis Trinckauf, Josey Curioni, Alessandra Opitz, Isabelle Winklhofer, Sebastian Huellner, Martin W. J Digit Imaging Original Paper The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed staging/restaging 18F-FDG PET/CT scans of 40 consecutive lung cancer patients with new brain metastases, confirmed by MRI. PET images were reconstructed using BSREM (β-values of 100, 200, 300, 400, 500, 600, 700) and OSEM. Two independent blinded readers (R1 and R2) evaluated each reconstruction using a 4-point scale for general image quality, noise, and lesion detectability. SUVmax of metastases, brain background, target-to-background ratio (TBR), and contrast recovery (CR) ratio were recorded for each reconstruction. Among all reconstruction techniques, differences in qualitative parameters were analyzed using non-parametric Friedman test, while differences in quantitative parameters were compared using analysis of variances for repeated measures. Cohen’s kappa (k) was used to measure inter-reader agreement. The overall detectability of brain metastases was highest for BSREM200 (R1: 2.83 ± 1.17; R2: 2.68 ± 1.32) and BSREM300 (R1: 2.78 ± 1.23; R2: 2.68 ± 1.36), followed by BSREM100, which had lower accuracy owing to noise. The highest median TBR was found for BSREM100 (R1: 2.19 ± 1.05; R2: 2.42 ± 1.08), followed by BSREM200 and BSREM300. Image quality ratings were significantly different among reconstructions (p < 0.001). The median quality score was higher for BSREM100-300, and both noise and metastases’ SUVmax decreased with increasing β-value. Inter-reader agreement was particularly high for the detectability of photopenic metastases and blurring (all k > 0.65). BSREM200 and BSREM300 yielded the best results for the detection of brain metastases, surpassing both BSREM400 and OSEM, typically used in clinical practice. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10278-021-00570-y. Springer International Publishing 2022-02-25 2022-06 /pmc/articles/PMC9156589/ /pubmed/35212859 http://dx.doi.org/10.1007/s10278-021-00570-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Liberini, Virginia
Pizzuto, Daniele A.
Messerli, Michael
Orita, Erika
Grünig, Hannes
Maurer, Alexander
Mader, Cäcilia
Husmann, Lars
Deandreis, Désirée
Kotasidis, Fotis
Trinckauf, Josey
Curioni, Alessandra
Opitz, Isabelle
Winklhofer, Sebastian
Huellner, Martin W.
BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title_full BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title_fullStr BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title_full_unstemmed BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title_short BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients
title_sort bsrem for brain metastasis detection with 18f-fdg-pet/ct in lung cancer patients
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9156589/
https://www.ncbi.nlm.nih.gov/pubmed/35212859
http://dx.doi.org/10.1007/s10278-021-00570-y
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