PET imaging of freely moving interacting rats
Bibliographic record
Abstract
Awake rat brain positron emission tomography (PET) has previously been developed to avoid the influence of anesthesia on the rat brain response. In the present work, we further the awake rat brain scanning methodology to establish simultaneous scanning of two interacting rats in a high resolution, large field of view PET scanner. Awake rat imaging methodology based on point source tracking was adapted to be used in a dedicated human brain scanner, the ECAT high resolution research tomograph (HRRT). Rats could freely run on a horizontal platform of 19.4 × 23 cm placed inside the HRRT. The developed methodology was validated using a motion resolution phantom experiment, 3 awake single rat [18F]FDG scans as well as an [18F]FDG scan of 2 interacting rats. The precision of the point source based motion tracking was 0.359 mm (standard deviation). Minor loss of spatial resolution was observed in the motion corrected reconstructions (MC) of the resolution phantom compared to the motion-free reconstructions (MF). The full-width-at-half-maximum of the phantom rods were increased by on average 0.37 mm in the MC compared to the MF. During the awake scans, extensive motion was observed with rats moving throughout the platform area. The average rat head motion speed was 1.69 cm/s. Brain regions such as hippocampus, cortex and cerebellum could be recovered in the motion corrected reconstructions. Relative regional brain uptake of MC and MF was strongly correlated (Pearson's r ranging from 0.82 to 0.95, p < 0.0001). Awake rat brain PET imaging of interacting rats was successfully implemented on the HRRT scanner. The present method allows a large range of motion throughout a large field of view as well as to image two rats simultaneously opening the way to novel rat brain PET study designs.
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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 | 0.000 |
| 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".