Enhancement of the signal-to-noise ratio in H2(15)O bolus PET activation images: a combined cold-bolus, switched protocol.
Bibliographic record
Abstract
UNLABELLED: To increase the signal-to-noise ratio (S/N) of H2(15)O bolus PET activation images, we designed and tested a data acquisition protocol that alters the relative distribution of tracer in the uptake and washout phases of the input function. This protocol enhances the S/N gains obtained with conventional switched protocols by combining task switching and the use of a large bolus of blood free of tracer (cold bolus). The cold bolus is formed by sequestering blood in the lower limbs with a double cuff before tracer injection. METHODS: The effect of a combined cold-bolus, switched protocol on the signal from activation images was first simulated using a compartmental model of the uptake of H2(15)O into the brain. Then, the effectiveness of the protocol was investigated in 4 healthy volunteers performing a language task. Each volunteer underwent scanning 12 times: 3 activation/ baseline and 3 baseline/activation scans using the conventional switched protocol and 3 activation/baseline and 3 baseline/activation scans using the combined cold-bolus, switched protocol. The S/N changes introduced when using the cold bolus were analyzed by comparing, across protocols, the magnitude and statistical significance of the activation foci associated with the execution of the language task identified in the averaged subtracted images, and by comparing image noise levels. RESULTS: In the simulated datasets, the combined protocol yielded a substantial increase in the activation signals for scan durations greater than 60 s, in comparison with equivalent signals yielded by the switched protocol alone. In the PET experiments, activation foci obtained using the combined protocol had significantly higher t statistic values than did equivalent foci detected using the conventional switched protocol (mean improvement, 36%). Analysis of the S/N in the averaged subtracted images revealed that the improvements in statistical significance of the activation foci were caused by increases in the signal magnitudes and not by decreases in overall image noise. CONCLUSION: We designed a data acquisition protocol for H2(15)O bolus PET activation studies that combines the use of a tracer-free bolus with a switched protocol. Simulated and experimental data suggest that this combined protocol enhances the S/N gains obtained with a conventional switched protocol. Implementation of the combined protocol in H2(15)O bolus activation studies was easy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".