Relationship between isotope half‐life and prostatic edema for optimal prostate dose coverage in permanent seed implants
Bibliographic record
Abstract
The robustness of treatment planning to prostatic edema for three different isotopes (125I, 103Pd, and 131Cs) is explored using dynamical dose calculations on 25 different clinical prostate cases. The treatment plans were made using the inverse planning by simulated annealing (IPSA) algorithm. The prescription was 144, 127, and 125 Gy for 125I, 131Cs, and 103Pd, respectively. For each isotope, three dose distribution schemes were used to impose different protection levels to the urethra: V120 = 0%, V150 = 0%, and V150 = 30%. Eleven initial edema values were considered ranging from 1.0 (no edema) to 2.0 (100%). The edema was assumed to resolve exponentially with time. The prostate volume, seed positions, and seed activity were dynamically tracked to produce the final dose distribution. Edema decay half-lives of 10, 30, and 50 days were used. A total of 675 dynamical calculations were performed for each initial edema value. For the 125I isotope, limiting the urethra V120 to 0% leads to a prostate D90 under 140 Gy for initial edema values above 1.5. Planning with urethra V150 at 0% provides a good response to the edema; the prostate D90 remains higher than 140 Gy for edema values up to 1.8 and a half-life of 30 days or less. For 103Pd, the prostate D90 is under 97% of the prescription dose for approximately 66%, 40%, and 30% of edema values for urethra V120 = 0%, V150 = 0%, and V150 = 30%, respectively. Similar behavior is seen for 131Cs and the center of the prostate becomes "cold" for almost all edema scenarios. The magnitude of the edema following prostate brachytherapy, as well as the half-life of the isotope used and that of the edema resorption, all have important impacts on the dose distribution. The 125I isotope with its longer half-life is more robust to prostatic edema. Setting up good planning objectives can provide an adequate compromise between organ doses and robustness. This is even more important since seed misplacements will contribute to further degrade dose coverage.
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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 | 0.003 |
| 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 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".