Evidence map›Paper›PMID 40839230›Full record

ArticlePhysical and engineering sciences in medicine2025

Monte Carlo prediction and experimental characterisation of long-lived waste byproducts arising from cyclotron production of zirconium-89 utilising a commercially available yttrium foil.

Andrew Chacon, Sylvia Gong, Artur Cichocki, Talia Enright, Harris Panopoulos, Nathan Sonnberger, Andrew M Scott, Graeme O'Keefe

Abstract read
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Article in Physical and engineering sciences in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Andrew ChaconDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia. andrew.chacon@austin.org.au.ORCID http://orcid.org/0000-0003-3939-0862
Sylvia GongDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Artur CichockiDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Talia EnrightDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Harris PanopoulosDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Nathan SonnbergerDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Andrew M ScottDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia.
Graeme O'KeefeDepartment of Molecular Imaging and Therapy, Austin Health, Heidelberg, Australia. graeme.okeefe@austin.org.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zirconium-89 is presently undergoing pre-clinical investigation for its potential application as a positron emission tomography (PET) theranostic radioisotope. A critical consideration in the increasing number of trials and eventual clinical implementations is a comprehensive understanding of the radioactive waste byproducts and their quantification. This study focuses on the investigation and characterisation of the waste isotopes generated during the production of Zirconium-89, employing a combination of Geant4 Monte Carlo simulation and experimental methodologies utilising commercially obtainable starting materials from Thermofisher. Post cyclotron production samples of waste were taken and measured using a high purity germanium detector. Subsequent spectrum analysis consistently revealed the presence of the following isotopes in units of kBq per GBq of Zirconium-89 produced: cobalt-56 (13 ± 2, 14 ± 2, 15 ± 1), cobalt-57 (0.087 ± 0.004, 0.097 ± 0.004, 0.086 ± 0.007), rhenium-183 (2.61 ± 0.06, 3.29 ± 0.06, 2.47 ± 0.09), scandium-48 (27 ± 0.9, 21.1 ± 0.4), yttrium-88 (0.67 ± 0.06, 1.1 ± 0.4, 0.73 ± 0.06) and zirconium-88 (90 ± 5, 1340 ± 60, 35 ± 2). All the waste isotopes were able to reasonably be estimated using Geant4 Monte Carlo simulations or the deviation was able to be justified. The repeatability and predictability of isotopes and activities will enable informed decision-making regarding storage and disposal procedures in accordance with local legislative requirements.

Indexed as

CyclotronsMonte Carlo MethodRadioactive WasteRadioisotopesYttriumZirconiumRadioactive WasteRadioisotopesYttriumZirconiumZirconium-89CyclotronPETWasteZr89

Identifiers

PMID40839230
PMCPMC12738615

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.