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Record W4385408211 · doi:10.1186/s40658-023-00564-5

A GATE simulation study for dosimetry in cancer cell and micrometastasis from the 225Ac decay chain

2023· article· en· W4385408211 on OpenAlexafffund
Helena Koniar, Cassandra Miller, Arman Rahmim, Paul Schaffer, Carlos Uribe

Bibliographic record

VenueEJNMMI Physics · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsSimon Fraser UniversityUniversity of British ColumbiaTRIUMF
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaTRIUMF
KeywordsAbsorbed doseRadionuclide therapyDosimetryRadionuclideNuclear medicineNucleusCytoplasmChemistryMedicinePhysicsNuclear physicsBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background Radiopharmaceutical therapy (RPT) with alpha-emitting radionuclides has shown great promise in treating metastatic cancers. The successive emission of four alpha particles in the 225Ac decay chain leads to highly targeted and effective cancer cell death. Quantifying cellular dosimetry for 225Ac RPT is essential for predicting cell survival and therapeutic success. However, the leading assumption that all 225Ac progeny remain localized at their target sites likely overestimates the absorbed dose to cancer cells. To address limitations in existing semi-analytic approaches, this work evaluates S-values for 225Ac’s progeny radionuclides with GATE Monte Carlo simulations. Methods The cellular geometries considered were an individual cell (10 µm diameter with a nucleus of 8 µm diameter) and a cluster of cells (micrometastasis) with radionuclides localized in four subcellular regions: cell membrane, cytoplasm, nucleus, or whole cell. The absorbed dose to the cell nucleus was scored, and self- and cross-dose S-values were derived. We also evaluated the total absorbed dose with various degrees of radiopharmaceutical internalization and retention of the progeny radionuclides 221Fr (t1/2 = 4.80 m) and 213Bi (t1/2 = 45.6 m). Results For the cumulative 225Ac decay chain, our self- and cross-dose nuclear S-values were both in good agreement with S-values published by MIRDcell, with per cent differences ranging from − 2.7 to − 8.7% for the various radionuclide source locations. Source location had greater effects on self-dose S-values than the intercellular cross-dose S-values. Cumulative 225Ac decay chain self-dose S-values increased from 0.167 to 0.364 GyBq−1 s−1 with radionuclide internalization from the cell surface into the cell. When progeny migration from the target site was modelled, the cumulative self-dose S-values to the cell nucleus decreased by up to 71% and 21% for 221Fr and 213Bi retention, respectively. Conclusions Our GATE Monte Carlo simulations resulted in cellular S-values in agreement with existing MIRD S-values for the alpha-emitting radionuclides in the 225Ac decay chain. To obtain accurate absorbed dose estimates in 225Ac studies, accurate understanding of daughter migration is critical for optimized injected activities. Future work will investigate other novel preclinical alpha-emitting radionuclides to evaluate therapeutic potency and explore realistic cellular geometries corresponding to targeted cancer cell lines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.075
GPT teacher head0.401
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2023
Admission routes2
Has abstractyes

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