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Record W4407572763 · doi:10.1117/12.3047309

A Monte Carlo-based assessment of a SPECT/CT system with a single photon counting detector: a feasibility study

2025· article· en· W4407572763 on OpenAlexaff
James Day, Xinchen Deng, Magdalena Bazalova‐Carter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMonte Carlo methodDetectorSingle-photon emission computed tomographyPhoton countingPhotonPhysicsMedical physicsComputer scienceNuclear medicineOpticsMedicineStatisticsMathematics

Abstract

fetched live from OpenAlex

Photon-counting computed tomography (CT) systems are recent advancements in imaging technology that enable the possibility of material-specific imaging. Since single-photon emission computed tomography (SPECT) traditionally utilizes photon-counting principles, performing the entire imaging procedure with a singular photon-counting detector (PCD) may be feasible. This has the potential to reduce system costs, eliminate co-registration issues, and decrease procedure times. Our study aims to determine the limits of visibility of a technetium-99m for SPECT/CT using a singular PCD system through a fixed focus collimator. Our methodology used the TOPAS and Geant4 simulation toolkit to model a CdTe photon-counting SPECT/CT system based on the performance of an XCounter Thor device with charge cloud width and charge collection efficiency taken into account. The SPECT source was a Tc-99m source with 25 MBq of activity. A 2D focused collimator composed of tungsten was designed for dual SPECT/CT imaging. The grid ratio varied from 20:1 to 60:1, and the optimal grid ratio was determined by the modulation transfer function (MTF) and the contrast-to-noise ratio (CNR). The optimal collimator ratio occurred at 50:1 or 40:1, according to the MTF and the CNR, respectively. There was a 1% difference in spatial resolution between a grid ratio of 50:1 and 60:1, suggesting that grids more aggressive than 50:1 are unnecessary for SPECT imaging. The CNR had a maximum value of 14.8+/-0.2 at a grid ratio of 40:1. These results were also qualitatively supported by the produced SPECT/CT images. In conclusion, our study confirms the feasibility of SPECT/CT with a singular photon-counting CT system. We found that a grid ratio of 40:1 maximized the CNR while maintaining a spatial resolution of 0.2 cycles/mm at an MTF value of 0.1. These findings provide a solid foundation for the future development and implementation of more efficient and cost-effective imaging systems.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.031
GPT teacher head0.355
Teacher spread0.324 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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