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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.
Afiliação
  • Gillett D; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. dg538@medschl.cam.ac.uk.
  • Marsden D; Cambridge Endocrine Molecular Imaging Group, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. dg538@medschl.cam.ac.uk.
  • Crawford R; Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Ballout S; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • MacFarlane J; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • van der Meulen M; Cambridge Endocrine Molecular Imaging Group, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Gillett B; Cambridge Endocrine Molecular Imaging Group, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Bird N; East Anglian Regional Radiation Protection Service, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Heard S; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Powlson AS; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Santarius T; Cambridge Endocrine Molecular Imaging Group, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Mannion R; Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Kolias A; Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Harper I; Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Mendichovszky IA; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Aloj L; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Cheow H; Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Bashari W; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Koulouri O; Department of Radiology, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
  • Gurnell M; Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
EJNMMI Phys ; 10(1): 34, 2023 Jun 01.
Article em En | MEDLINE | ID: mdl-37261547
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 (ß) from 50 to 1000) were tested. Images were analyzed quantitatively and qualitatively by eight expert readers. Quantitatively, signal was the highest using BPL with ß = 50; noise was the lowest using BPL with ß = 1000; contrast was the highest using BPL with ß = 100. The qualitative review found that accuracy and confidence were the highest when using BPL with ß = 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 ß value of 400; in addition, for small (< 4 mm) tumors with low contrast (21 or 51), sensitivity may be improved using a ß value of 100. Together, these findings should increase tumor detection and confidence in reporting scans.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Revista: EJNMMI Phys Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Revista: EJNMMI Phys Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido