Time-of-Flight Requirements to Mitigate Blurring Induced by Annihilation Photon Acollinearity
Bibliographic record
Abstract
One of the limiting factors of spatial resolution in positron emission tomography (PET) imaging is annihilation photon acollinearity (APA). For whole-body PET scanners, APA induces a blur ranging from 1.7 to 2.2 mm FWHM. For long axial field-of-view (FOV) scanners, this range increases even more, depending on the maximum ring difference. It was previously shown that perfect time-of-flight (TOF) resolution sharpens the APA-induced blur by altering its expected Gaussian shape into a profile resembling a 1/r function, thereby reducing its contribution to spatial resolution loss. This suggests that the conventional theoretical limit of PET spatial resolution could be overcome if sufficient TOF resolution can be achieved. However, the requirements to achieve an observable gain in spatial resolution have yet to be explored. We propose an investigation of these requirements for whole-body and long axial FOV scanners, in terms of TOF resolution and count statistics. Using a fictive 81-cm diameter scanner with 2-mm wide detectors, we show that ultrafast TOF resolution-13 ps FWHM-enables an observable gain in spatial resolution for a range of count statistics. In addition, we show that lower TOF resolutions (i.e., higher TOF values of 27 or 67 ps) could mitigate APA for the oblique tubes of response of long axial FOV systems subjected to larger APA blurring. This last observation is of particular interest as it suggests that the nonstationary nature of spatial resolution in PET imaging can be further mitigated when such TOF precision is achieved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".