Sheet beam x‐ray fluorescence computed tomography (XFCT) imaging of gold nanoparticles
Bibliographic record
Abstract
PURPOSE: X-ray fluorescence computed tomography (XFCT) experiments have typically used pencil beams for data acquisition, which yielded good quality images of gold nanoparticles (AuNP) but prolonged the imaging time. Here we propose three novel collimator geometries for use with faster sheet beam XFCT data acquisition. The feasibility of a multipinhole, parallel, and converging collimator was investigated in a Monte Carlo study. METHODS: A cylindrical water phantom with 2 cm in diameter and 3 cm in height containing 0.5-2 mm diameter vials with 0.4%-1.6% AuNP concentrations was modelled by FLUKA. A 15 and 81 keV monoenergetic x-ray sheet beam of 0.4 mm in width was used to image the phantom with L-shell and K-shell XFCT, respectively, with a dose of 30 mGy. The collimator thickness for L-shell and K-shell data acquisition was 3.3 and 5.1 mm, respectively. The XFCT images resulting from three collimator geometries were generated using the maximum likelihood expectation maximization (MLEM) iterative reconstruction method. With a resolution of 0.4 mm they were corrected for x-ray attenuation. The sheet beam XFCT images were compared against pencil beam geometry images that were generated using 55 translations. To assess image quality, the contrast-to-noise ratio (CNR) was evaluated for each vial. The Rose criterion was used to determine the lowest AuNP concentration detectable for each image. RESULTS: Among the three collimator geometry types, the sheet beam L-shell and K-shell parallel collimator XFCT images yielded AuNP sensitivity limits at 0.09% and 0.08%, respectively, for a 2 mm diameter vial. The AuNP sensitivity limits of the pencil beam XFCT images were 0.07% and 0.01% for L-shell and K-shell XFCT, respectively. The L-shell parallel collimator AuNP imaging sensitivity approached that of the pencil beam geometry with a 55-fold reduction in imaging time. The AuNP sensitivity limits for the 1 mm diameter vial for the L-shell and K-shell parallel collimator XFCT images were 0.19% and 0.16%, respectively, and those of the pencil beam XFCT images were 0.08% and 0.01% for L-shell and K-shell XFCT, respectively. The remaining two collimator geometries resulted in a lower CNR and poorer image quality. For a 2 mm diameter vial, the AuNP sensitivity limits for the L-shell and K-shell multipinhole collimator XFCT images were 0.23% and 0.52%, respectively, while for the L-shell and K-shell converging collimator XFCT images the AuNP sensitivity limits were 0.38% and 0.13%, respectively. CONCLUSION: This work demonstrates the feasibility of sheet beam L-shell XFCT imaging for small animal studies using parallel-oriented lead collimators which can detect AuNP concentrations approaching the level of pencil beam images with reduced imaging time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".