Scanning rats on the high resolution research tomograph (HRRT): A comparison study with a dedicated micro‐PET
Bibliographic record
Abstract
PURPOSE: The Siemens ECAT high resolution research tomograph (HRRT) is a dedicated human brain PET camera with a 6% absolute sensitivity and a (2.3 mm)(3) spatial resolution, improving to (1.8 mm)(3) when point spread function (PSF) modeling algorithms are used. These values are very close to those of dedicated small animal PET cameras such as the Siemens microPET FOCUS 120 (F120). The larger axial and transaxial field of view of the HRRT compared to the F120 allows, in principle, for simultaneous imaging of several rodents thus potentially reducing scanning costs and time. This study investigates the feasibility of using the HRRT for quantitative small animal brain studies. METHODS: We compare, in terms of magnitude, reproducibility, and asymmetry, the nondisplaceable tissue input binding potentials (BP(ND)) in the striata obtained from [(11)C]methylphenidate scans of the same rats imaged on both the F120 and the HRRT. The animal studies are complemented by a phantom study aimed at investigating noise properties relevant to the size of typical regions of interest used in rat brain image analysis. RESULTS: (i) The BP(ND) values obtained from HRRT data are lower than those obtained on the F120 by 38% when PSF modeling is not used, while they are 7% higher with PSF modeling. (ii) The within animal reproducibility on the HRRT is 18% without PSF modeling, worse than the 6% reproducibility on the F120, and is even further degraded to a value of 27% with the use of PSF modeling. (iii) The asymmetry between the left and right striatum in healthy rats worsens from 4.7% in the F120 images to 7.8% in the HRRT images reconstructed without PSF modeling, and is even worse with a value of 14.8% when PSF modeling is used. (iv) Overshooting artifacts and clumpiness in the noise structure of the HRRT images reconstructed with PSF modeling are clearly visible. CONCLUSIONS: The spatial resolution achieved on the HRRT without the use of resolution recovery techniques is not sufficient to allow for reliable quantitative small animal brain imaging. While PSF modeling in the reconstruction of the HRRT images in principle improves the resolution close to the level of the F120, it also introduces small scale nonuniformity artifacts and overshooting artifacts which preclude reliable quantitative small animal brain imaging on the HRRT.
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".