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Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors

BACKGROUND: Image optimization is a key step in clinical nuclear medicine, and phantoms play an essential role in this process. However, most phantoms do not accurately reflect the complexity of human anatomy, and this presents a particular challenge when imaging endocrine glands to detect small (of...

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Autores principales: Gillett, Daniel, Marsden, Daniel, Crawford, Rosy, Ballout, Safia, MacFarlane, James, van der Meulen, Merel, Gillett, Bethany, Bird, Nick, Heard, Sarah, Powlson, Andrew S., Santarius, Thomas, Mannion, Richard, Kolias, Angelos, Harper, Ines, Mendichovszky, Iosif A., Aloj, Luigi, Cheow, Heok, Bashari, Waiel, Koulouri, Olympia, Gurnell, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234958/
https://www.ncbi.nlm.nih.gov/pubmed/37261547
http://dx.doi.org/10.1186/s40658-023-00552-9
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author Gillett, Daniel
Marsden, Daniel
Crawford, Rosy
Ballout, Safia
MacFarlane, James
van der Meulen, Merel
Gillett, Bethany
Bird, Nick
Heard, Sarah
Powlson, Andrew S.
Santarius, Thomas
Mannion, Richard
Kolias, Angelos
Harper, Ines
Mendichovszky, Iosif A.
Aloj, Luigi
Cheow, Heok
Bashari, Waiel
Koulouri, Olympia
Gurnell, Mark
author_facet Gillett, Daniel
Marsden, Daniel
Crawford, Rosy
Ballout, Safia
MacFarlane, James
van der Meulen, Merel
Gillett, Bethany
Bird, Nick
Heard, Sarah
Powlson, Andrew S.
Santarius, Thomas
Mannion, Richard
Kolias, Angelos
Harper, Ines
Mendichovszky, Iosif A.
Aloj, Luigi
Cheow, Heok
Bashari, Waiel
Koulouri, Olympia
Gurnell, Mark
author_sort Gillett, Daniel
collection PubMed
description BACKGROUND: Image optimization is a key step in clinical nuclear medicine, and phantoms play an essential role in this process. However, most phantoms do not accurately reflect the complexity of human anatomy, and this presents a particular challenge when imaging endocrine glands to detect small (often subcentimeter) tumors. To address this, we developed a novel phantom for optimization of positron emission tomography (PET) imaging of the human pituitary gland. Using radioactive 3D printing, phantoms were created which mimicked the distribution of (11)C-methionine in normal pituitary tissue and in a small tumor embedded in the gland (i.e., with no inactive boundary, thereby reproducing the in vivo situation). In addition, an anatomical phantom, replicating key surrounding structures [based on computed tomography (CT) images from an actual patient], was created using material extrusion 3D printing with specialized filaments that approximated the attenuation properties of bone and soft tissue. RESULTS: The phantom enabled us to replicate pituitary glands harboring tumors of varying sizes (2, 4 and 6 mm diameters) and differing radioactive concentrations (2 ×, 5 × and 8 × the normal gland). The anatomical phantom successfully approximated the attenuation properties of surrounding bone and soft tissue. Two iterative reconstruction algorithms [ordered subset expectation maximization (OSEM); Bayesian penalized likelihood (BPL)] with a range of reconstruction parameters (e.g., 3, 5, 7 and 9 OSEM iterations with 24 subsets; BPL regularization parameter (β) from 50 to 1000) were tested. Images were analyzed quantitatively and qualitatively by eight expert readers. Quantitatively, signal was the highest using BPL with β = 50; noise was the lowest using BPL with β = 1000; contrast was the highest using BPL with β = 100. The qualitative review found that accuracy and confidence were the highest when using BPL with β = 400. CONCLUSIONS: The development of a bespoke phantom has allowed the identification of optimal parameters for molecular pituitary imaging: BPL reconstruction with TOF, PSF correction and a β value of 400; in addition, for small (< 4 mm) tumors with low contrast (2:1 or 5:1), sensitivity may be improved using a β value of 100. Together, these findings should increase tumor detection and confidence in reporting scans. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-023-00552-9.
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spelling pubmed-102349582023-06-03 Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors Gillett, Daniel Marsden, Daniel Crawford, Rosy Ballout, Safia MacFarlane, James van der Meulen, Merel Gillett, Bethany Bird, Nick Heard, Sarah Powlson, Andrew S. Santarius, Thomas Mannion, Richard Kolias, Angelos Harper, Ines Mendichovszky, Iosif A. Aloj, Luigi Cheow, Heok Bashari, Waiel Koulouri, Olympia Gurnell, Mark EJNMMI Phys Original Research BACKGROUND: Image optimization is a key step in clinical nuclear medicine, and phantoms play an essential role in this process. However, most phantoms do not accurately reflect the complexity of human anatomy, and this presents a particular challenge when imaging endocrine glands to detect small (often subcentimeter) tumors. To address this, we developed a novel phantom for optimization of positron emission tomography (PET) imaging of the human pituitary gland. Using radioactive 3D printing, phantoms were created which mimicked the distribution of (11)C-methionine in normal pituitary tissue and in a small tumor embedded in the gland (i.e., with no inactive boundary, thereby reproducing the in vivo situation). In addition, an anatomical phantom, replicating key surrounding structures [based on computed tomography (CT) images from an actual patient], was created using material extrusion 3D printing with specialized filaments that approximated the attenuation properties of bone and soft tissue. RESULTS: The phantom enabled us to replicate pituitary glands harboring tumors of varying sizes (2, 4 and 6 mm diameters) and differing radioactive concentrations (2 ×, 5 × and 8 × the normal gland). The anatomical phantom successfully approximated the attenuation properties of surrounding bone and soft tissue. Two iterative reconstruction algorithms [ordered subset expectation maximization (OSEM); Bayesian penalized likelihood (BPL)] with a range of reconstruction parameters (e.g., 3, 5, 7 and 9 OSEM iterations with 24 subsets; BPL regularization parameter (β) from 50 to 1000) were tested. Images were analyzed quantitatively and qualitatively by eight expert readers. Quantitatively, signal was the highest using BPL with β = 50; noise was the lowest using BPL with β = 1000; contrast was the highest using BPL with β = 100. The qualitative review found that accuracy and confidence were the highest when using BPL with β = 400. CONCLUSIONS: The development of a bespoke phantom has allowed the identification of optimal parameters for molecular pituitary imaging: BPL reconstruction with TOF, PSF correction and a β value of 400; in addition, for small (< 4 mm) tumors with low contrast (2:1 or 5:1), sensitivity may be improved using a β value of 100. Together, these findings should increase tumor detection and confidence in reporting scans. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-023-00552-9. Springer International Publishing 2023-06-01 /pmc/articles/PMC10234958/ /pubmed/37261547 http://dx.doi.org/10.1186/s40658-023-00552-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Research
Gillett, Daniel
Marsden, Daniel
Crawford, Rosy
Ballout, Safia
MacFarlane, James
van der Meulen, Merel
Gillett, Bethany
Bird, Nick
Heard, Sarah
Powlson, Andrew S.
Santarius, Thomas
Mannion, Richard
Kolias, Angelos
Harper, Ines
Mendichovszky, Iosif A.
Aloj, Luigi
Cheow, Heok
Bashari, Waiel
Koulouri, Olympia
Gurnell, Mark
Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title_full Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title_fullStr Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title_full_unstemmed Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title_short Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors
title_sort development of a bespoke phantom to optimize molecular pet imaging of pituitary tumors
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234958/
https://www.ncbi.nlm.nih.gov/pubmed/37261547
http://dx.doi.org/10.1186/s40658-023-00552-9
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