Prostatic edema in permanent prostate implants: Dynamical dosimetry taking volume changes into account
Bibliographic record
Abstract
The purpose of this study is to determine the impact of edema on the dose delivered to the target volume. An evaluation of the edema characteristics was first made, and then a dynamical dosimetry algorithm was developed and used to compare its results to a standard clinical (static) dosimetry. Source positions and prostate contours extracted from 66 clinical cases on images taken at different points in time (planning, implant day, post-implant evaluation) were used, via the mean interseed distance, to characterize edema [initial increase (deltar0), half-life (tau)]. An algorithm was developed to take into account the edema by summing a time series of dose-volume histograms (DVHs) with a weight based on the fraction of the dose delivered during the time interval considered. The algorithm was then used to evaluate the impact of edema on the dosimetry of permanent implants by comparing its results to those of a standard clinical dosimetry. The volumetric study yielded results as follows: the initial prostate volume increase was found to be 1.58 (ranging from 1.15 to 2.48) and the edema half-life, approximately 30 days (range: 3 to 170 days). The dosimetric differences in D90 observed between the dynamic dosimetry and the clinical one for a single case were up to 15 Gy and depended on the edema half-life and the initial volume increase. The average edema half-life, 30 days, is about 3 times longer than the previously reported 9 days. Dosimetric differences up to 10% of the prescription dose are observed, which can lead to differences in the quality assertion of an implant. The study of individual patient edema resorption with time might be necessary to extract meaningful clinical correlation or biological parameters in permanent implants.
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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".