Technical Note: Empirical altitude correction factors for well chamber measurements of permanent prostate and breast seed implant sources
Bibliographic record
Abstract
Purpose Previous studies in the literature have measured an altitude effect for low‐energy brachytherapy seeds; a correction factor applied in addition to PTP to account for the breakdown of Bragg–Gray cavity theory at low energies in well‐type ionization chambers. In clinical practice, many centers use altitude correction factors that are not seed‐model‐specific. The purpose of this work is to present altitude correction factors for several seed models without documented factors in the literature. Methods An in‐house constructed pressure vessel was used with a well‐type ionization chamber to measure the air‐kerma strength of the IsoAid Advantage (Pd‐103), Theragenics AgX100 (I‐125), and Nucletron selectSeed (I‐125) at a pressure range representative of those encountered worldwide. The TheraSeed 200 (Pd‐103) was also measured for comparison to the originally published correction factor for validation of the experimental process. When correction factors derived in this work were within experimental uncertainties of those published, no new correction factors were proposed. Results The three seed models measured herein all demonstrated a similar response to change in pressure as previously documented in the literature with the HDR 1000 Plus well‐type ionization chamber. Correction factors of the functional form , consistent with those previously published, were found to be appropriate for these seed models. A new correction factor is proposed for the Theragenics AgX100 and Nucletron selectSeed (k1 = 0.0417, k2 = 0.479). The IsoAid Advantage, however, agreed to within uncertainty with the published altitude correction factor for the TheraSeed 200; thus the application of the same correction factor is appropriate (k1 = 0.0241, k2 = 0.562). Conclusions This work presents altitude correction factors for three permanent implant brachytherapy seed models in clinical use. This will allow clinics to utilize model‐specific factors, reducing systematic errors in their air‐kerma strength verifications.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".