Dosimetry considerations for Endovascular Photo-activated Ablation (EPA) aimed at downstaging locally advanced pancreatic cancers.
Bibliographic record
Abstract
Significance Targeting pancreatic tumours immediately adjacent to major blood vessels aims to render patients suitable for surgery to improve prognosis. We are developing endovascular photo-activated ablation (EPA) as an innovative form of photodynamic therapy (PDT), to achieve this goal. However, it requires careful light and drug dosimetry. Approach Building on reported pancreatic tumour response following interstitial BPD-mediated PDT, the tissues’ responsivities were determined and applied to in silico dosimetry studies. Monte Carlo simulations were employed to determine the endovascular power delivery required to achieve necrotic radii of 5 to 15 mm beyond the arterial or venous wall as a function of the vessel lumen diameter. Results Pancreatic cancer necrosis up to 15mm deep is attainable adjacent to the blood vessel, albeit with limited selectivity to normal pancreatic tissues. Depending on the vessel’s location, simulations should include adjacent organs. Conclusions Simulations can assist in EPA dose estimations to downgrade pancreatic cancer.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".