Development of small, cost‐efficient scintillating fiber detectors for automated synthesis of positron emission tomography radiopharmaceuticals
Bibliographic record
Abstract
Abstract Background Radiolabeling is critical in complex chemical reactions involving positron emission tomography (PET) radiotracer production. The process is now automated within a synthesis module to enhance efficiency and reduce radiation exposure. The key to this automation is the use of radiation detectors to monitor radioactivity transfer and ensure the progression of reactions. However, the high cost of these detectors has motivated the need for a more affordable alternative. Purpose This study aimed to develop a compact and cost‐efficient detector using scintillating fibers and silicon photomultipliers (SiPMs) to track radioactivity throughout PET radiotracer production. Methods Monte Carlo simulations were performed with the Geant4‐based M‐TAG software for four detector geometries (single fiber, single fiber with bolus, 16‐fiber bundle, and spiral) to optimize the detector construction for better detection efficiency. The simulations scored the energy deposited into the scintillating fibers per simulated particle, which was used to estimate the expected voltage pulse height from the SiPM considering the total light collection efficiency. Based on the simulation results, two detector configurations (16‐fiber bundle and spiral fiber) were constructed using plastic scintillating fibers, optical fibers, a 6 mm 6 mm SiPM, and commonly available electronic components. The detectors were calibrated using a Fluorine‐18 () source with typical activity levels used in radiotracer production. Detector performances were subsequently evaluated through linearity tests and measurement uncertainty assessments. Errors up to were considered acceptable for troubleshooting purposes. Results The calibration curves showed a linear response with changing activity for both detectors. The calibrated detectors offered real‐time activity measurements ranging from 0.10 to 49.41 GBq, with a 3‐s refresh rate. In the activity range above 0.145 GBq, the uncertainties were less than for both the 16‐fiber and spiral configurations. The spiral detector recorded a signal with a half‐life of min, closely aligning with the reference half‐life of . Conclusions Cost‐efficient plastic scintillation fiber detectors were developed to facilitate the troubleshooting of automated synthesis of PET radiotracers.
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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".