SU‐E‐T‐265: Reducing Pacemaker Doses with a Lead Sheet: A Multi‐Detector Study
Bibliographic record
Abstract
PURPOSE: Evaluate the usability of lead shielding to reduce the dose to pacemakers. The efficiency and risk of this type of skin block will be presented. METHODS: A solid water phantom was used and all measurements were made at a depth of 0.5 cm for 6 MV and 23 MV photon beams. Measurements were performed with a parallel plate ion chamber and with a plastic scintillation detector (PSD) prototype. Measurements were made for fields of 10, 20 and 30 cm square. For every field, measurements were made in increment of 5 cm from the center of the field to the edge of the 60 cm long phantom for anterior and posterior beams. All measures have been made with and without a 1.6 mm of lead shielding wrapped in a thermoplastic. RESULTS: For all measurements, both detectors agree to 0.6%, well within the uncertainties of the detectors. With antero-posterior fields, the benefit of shielding is more important at 23MV (reduction of dose by65%) compared to 6MV (reduction of dose by 46%) when the shielding is out of the field. For distances larger than 35 cm, no benefits are measured. In the case were the lead is completely inside the fields, the dose is increased by the presence of shielding. The same observation is made for postero-anterior fields. For shielding out of field, the dose is slightly increased. CONCLUSIONS: The used of lead shielding with antero-posterior field is advised and provided an easy way to decrease dose to pacemaker. For a postero-anterior field, it is preferable to avoid shielding, but it could be used if it stays outside fields in the case of a multiple beams treatment. PSD has been shown to be an excellent candidate for in vivo monitoring dose to pacemakers and also site like foetus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".