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

Autor: Daniel Gillett, Daniel Marsden, Rosy Crawford, Safia Ballout, James MacFarlane, Merel van der Meulen, Bethany Gillett, Nick Bird, Sarah Heard, Andrew S. Powlson, Thomas Santarius, Richard Mannion, Angelos Kolias, Ines Harper, Iosif A. Mendichovszky, Luigi Aloj, Heok Cheow, Waiel Bashari, Olympia Koulouri, Mark Gurnell
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: EJNMMI Physics, Vol 10, Iss 1, Pp 1-23 (2023)
Druh dokumentu: article
ISSN: 2197-7364
DOI: 10.1186/s40658-023-00552-9
Popis: Abstract 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 11C-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 (
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