Impact of edema and seed movement on the dosimetry of prostate seed implants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article summarizes current knowledge concerning the characterization of prostatic edema and intra-prostatic seed movement as these relate to dosimetry of permanent prostate implants, and reports the initial application to clinical data of a new edema model used in calculating pre- and post-implant dose distributions. Published edema magnitude and half-life parameters span a broad range depending on implant technique and measurement uncertainty, hence clinically applicable values should be determined locally. Observed intra-prostatic seed movements appear to be associated with particular aspects of implant technique and could be minimized by technique modification. Using an extended AAPM TG-43 formalism incorporating the new edema model, relative dose error RE associated with neglecting edema was calculated for three I-125 seed implants (18.9 cc, 37.6 cc, 60.2 cc) performed at our center. Pre- and post-plan RE average values and ranges in a 50 × 50 × 50 mm(3) calculation volume were similar at ~2% and ~0-3.5%, respectively, for all three implants; however, the spatial distribution of RE varied for different seed configurations. Post-plan values of D90 and V100 for prostate were reduced by ~2% and ~1%, respectively. In cases where RE is not clinically negligible as a consequence of large edema magnitude and / or use of Pd-103 seeds, the dose calculation method demonstrated here can be applied to account for edema explicitly and there by improve the accuracy of clinical dose estimates.
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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 | 0.009 | 0.002 |
| 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 | 0.000 | 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 it