Evaluation of an automatic needle‐loading system
Bibliographic record
Abstract
The purpose of this paper is to evaluate the dosimetric capabilities and the radiation protection (RP) performance of a new automatic needle-loading system for permanent prostate implants, the Isoloader (Mentor Corp.). The unit has been used in more than 100 clinical cases at our institution. The Isoloader is a computerized workstation that allows automated seed testing by a solid-state CdZnTe radiation detector and loading in surgical needles. The seeds are received in a shielded and ready-to-use cartridge. Radiation protection measurements were done on a cartridge filled with 67 (125)I seeds and during dosimetric seed verification and needle loading. The reproducibility of the detector was tested and its accuracy was determined by comparison to specified activities of six calibration seeds and to their measurements in a calibrated well-chamber (WC). Finally, the times required to complete dosimetric verification and needle loading were evaluated. The cartridge was found to be adequately shielded, since no significant amount of radiation was detected around it. Radiation during seed assay was found to be worst at the cartridge's bottom, where it has a value of 15.2 microSv/h (1.4 microSv/h at 10 cm). For the needle-loading task, measurements were performed with a typical needle (three seeds) at the shielded needle holder surface yielding 307.2 microSv/h (8.3 microSv/h at 20 cm). Seed dosimetric verification takes an average of 15 s/seed, while it takes a mean time of 50 s/needle to complete the loading task. Measurements of the six seed activities were within 0.65% of the ordered activities and 1.9% higher on average than those from the WC (min = 0.7%; max = 3.5%). The reproducibility of the measurements of the CdZnTe detector was excellent, with an average of 0.01% of deviation from a reference measurement (N = 120; = 1.9%). We therefore conclude that the Isoloader is a safe, fast, and effective needle-loading system.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".