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Record W4416391065 · doi:10.1016/j.pdpdt.2025.105062

Dosimetry considerations for Endovascular Photo-activated Ablation (EPA) aimed at downstaging locally advanced pancreatic cancers.

2025· article· en· W4416391065 on OpenAlexaff
Lothar Lilge, Alain García Vázquez, Tina Saeidi, Juan M. Verde, Fanélie Wanert, Irene Alexandra Spiridon, Axel Schmid, Lee L. Swanström, Stephen G. Bown, Arjen Bogaards

Bibliographic record

VenuePhotodiagnosis and Photodynamic Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPancreatic cancerDosimetryAblationLumen (anatomy)Cadaveric spasmPancreas

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.309
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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