SU‐E‐T‐337: Intensity Modulated Brachytherapy for Rectal Cancer Using A Novel Grooved Shielding Design
Bibliographic record
Abstract
Purpose: To create a novel HDR (192‐Ir) brachytherapy applicator for treatment of rectal carcinomas that uses tungsten shielding to make it dosimetrically superior to all commercially available applicators, despite being no larger than them. Methods: A set of 16 new applicators were designed and simulated using Monte Carlo (MCNPX). All designs were made of a 16‐mm diameter, high density tungsten alloy cylinder with inset grooves running along its length for the source to travel along. The designs varied regarding the number and depth of these grooves. Each design was optimized on 36 clinically treated plans (using 8‐channel Intracavitary Mold Applicator (Nucletron)) with asymmetrical CTVs, on in‐house written intensity modulated brachytherapy planning optimization software. Additionally, a 10 channel device with two channels per groove at varying depths was considered. All results were compared against the clinically treated plans. Results: First, all device designs outperformed the Intracavitary Mold Applicator in EVERY metric, except the total dwell times (about 30% increase). There were clear but relative tradeoffs regarding both the number of channels and the depth of each channel. Overall, the 12‐channel, 1‐mm depth design had the best results of the simpler designs, sparing the healthy rectal tissues the most while achieving comparable CTV coverage. All designs significantly outperformed the clinically treated plans using the Intracavitary Mold Applicator. Conclusions: Our extensive simulations and planning showed that our device designs have the ability to conform to the CTV and spare OAR with previously unmatched quality compared to existing commercial brachytherapy devices.
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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 | 0.000 | 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) | 0.001 | 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".