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Record W2567157880

Investigation of the impact on image resolution of trace impurities found in cyclotron-produced 99mTc pertechnetate

2015· article· en· W2567157880 on OpenAlexaffabout
Xinchi Hou, Jesse Tanguay, François Bénard, Milan Vuckovic, Ken Buckley, Paul Schaffer, Thomas J. Ruth, A. Ćeller

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsTRIUMFBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsCollimatorCyclotronFull width at half maximumPhysicsScintillatorPertechnetateDetectorOpticsOptical transfer functionNuclear medicineNuclear physicsTechnetiumElectronMedicine
DOInot available

Abstract

fetched live from OpenAlex

1749 Objectives Cyclotron-produced 99mTc pertechnetate (CPP) is an alternative to generator-produced 99mTc pertechnetate (GPP) but will contain very small quantities of other radioactive Tc isotopes1,2 that emit high-energy (>500 keV) γ-photons. These photons may penetrate collimator septa and deposit energy in the scintillator. The objective of this study was to quantify the effect of Tc impurities on the image spatial resolution. Methods We quantified spatial resolution in terms of the full width half maximum (FWHM) of the point spread function (PSF) and the modulation transfer function (MTF) of the imaging system. The PSF and MTF of CPP were estimated from Monte Carlo (GATE) simulations of point sources located 20 cm from the center of the detector. Five sources, which contained increasing proportion of radioactive Tc impurities, were simulated. The quantities of other Tc isotopes were established to correspond to increased patient radiation doses of 0%, 10%, 30% and 100% over pure 99mTc. The LEHR collimator and 140±10% keV window were used for simulation. Results The FWHM increased by Conclusions Impurities present in CPP may increase the FWHM of the PSF and result in a drop of MTF at low-frequencies. However, for product meeting radionuclide purity specifications that are proposed to be used in clinical practice ( Research Support This work was supported by Natural Resources Canada through the Non-reactor-based Isotope Supply Contribution Program and TRIUMF core funding.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.344
Teacher spread0.285 · 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 designBench or experimental
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

Citations1
Published2015
Admission routes2
Has abstractyes

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