SFEBES2023 Oral Poster Presentations Neuroendocrinology and Pituitary (4 abstracts)
Optimisation of molecular imaging for pituitary tumours using a radioactive phantom
Daniel Gillett 1,2 , James MacFarlane 1 , Linus Haberbosch 3,4,1 , Rosy Crawford 2 , Safia Ballout 2 , Daniel Marsden 5 & Mark Gurnell 1,6
1Cambridge Endocrine Molecular Imaging Group, University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom. 2Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom. 3Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health; Department of Endocrinology and Metabolism, Berlin, Germany. 4Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Digital Clinician Scientist Program, Berlin, Germany. 5Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, United Kingdom. 6Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Addenbrooke’s Hospital, Hills Road, Cambridge, United Kingdom
Background: Image reconstruction is a key step for the accurate interpretation of positron emission tomography (PET) scans. Nuclear medicine phantoms play a critical role in this process. However, existing phantoms (based on simple geometric shapes) do not reflect the complexity of sellar/parasellar anatomy. We therefore created a novel pituitary phantom and examined the impact of image optimisation on the detection of microadenomas, using 11C-methionine PET scans from patients with Cushing Disease who had previously undergone surgery.
Methods: Using radioactive 3D-printing, a bespoke pituitary phantom was created as previously reported (Gillett, 2023). The phantom replicated pituitary glands harbouring tumors of differing sizes (2, 4 and 6 mm diameters) and radioactive concentrations (2×, 5× and 8× the background normal gland). The anatomical phantom, housing the normal gland and embedded tumour, closely approximated the attenuation properties of surrounding bone and soft tissue. Following identification of optimal reconstruction parameters, these were retrospectively applied to PET scans from a cohort of patients with surgically-confirmed microadenomas, and assessed in blinded fashion by expert readers.
Results: Consistent with our previous findings, the optimal parameters for molecular pituitary imaging used a Bayesian penalised likelihood (BPL) iterative reconstruction algorithm, with time of flight, point spread function correction, and regularisation (β) parameter values of 400 or 100 (for tumours <4 mm diameter). These parameters were then applied retrospectively to preoperative scans from a cohort of patients with pituitary corticotroph microadenomas, in whom subsequent transsphenoidal surgery had confirmed the location of the tumour. In each case, reader confidence in identifying the correct location of the tumour was increased using the optimised reconstruction parameters. Importantly, no false positive calls were made using a negative control.
Conclusions: We have shown how a novel pituitary phantom can enhance detection of small corticotroph microadenomas using molecular PET imaging.
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Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
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