A New Tool for Molecular Imaging: The Microvolumetric Blood Counter
Bibliographic record
Abstract
UNLABELLED: Radiotracer kinetic modeling in small animals with PET allows absolute quantification of physiologic and biochemical processes in vivo. It requires blood and tissue tracer concentrations as a function of time. Manual sampling, the reference method for blood tracer concentration measurements, requires fairly large amounts of blood besides being technically difficult and time-consuming. An automated microvolumetric beta blood counter (microBC) was designed to circumvent these limitations by measuring the blood activity in real time with PET scanning. METHODS: The microBC uses direct beta-particle detection to reduce its footprint and is entirely remote controlled for sampling protocol selection and real-time monitoring of measured parameters. Sensitivity has been determined for the most popular PET radioisotopes ((18)F, (13)N, (11)C, (64)Cu). Dispersion within the sampling catheter has been modeled to enable automatic correction. Blood curves obtained with the microBC were compared with manual samples and PET-derived data. The microBC was used to estimate the myocardial blood flow (MBF) of mice injected with (13)N-ammonia and to compare the myocardial metabolic rate of glucose (MMRG) of rats injected with (18)F-FDG for arterial and venous cannulation sites. RESULTS: The sensitivity limit ranges from 3 to 104 Bq/microL, depending on the isotope and the catheter used, and was found to be adequate for most small-animal studies. Automatic dispersion correction appears to be a good approximation of dispersion-free reference curves. Blood curves sampled with the microBC are well correlated with curves obtained from manual samples and PET images. With correction for dispersion, the MBF of anesthetized mice at rest was found to be 4.84 +/- 0.5 mL/g/min, which is comparable to values found in the literature for rats. MMRG values derived from the venous blood tracer concentration are underestimated by 60% as compared with those derived from arterial blood. CONCLUSION: The microBC is a compact automated counter allowing real-time measurement of blood radioactivity for pharmacokinetic studies in animals as small as mice. Reliable and reproducible, the device makes it possible to increase the throughput of pharmacokinetic studies with reduced blood sample handling and staff exposure, contributing to speed up new drug development and evaluation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".