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Record W7084030295 · doi:10.1364/ecbo.2025.m1a.2

PDT dosimetry considerations for Endovascular PDT aimed at downstage “Borderline Resectable” pancreatic cancers

2025· article· en· W7084030295 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPancreatic cancerPhotodynamic therapyDosimetryLumen (anatomy)CancerPancreatic headPancreas

Abstract

fetched live from OpenAlex

Targeting pancreatic tumours immediately adjacent to major blood vessels aims to render patients suitable for standard surgical intervention to improve patient prognosis. Delivering the Photodynamic Therapy light endovascularly may achieve this goal, but it requires careful light and drug dosimetry. Building on reported pancreatic tumour and tissue response following interstitial BPD-mediated PDT, the tissues’ responsivities were determined and applied to in silico PDT 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. 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. Pre-PDT treatment simulations can assist in designing endovascular PDT 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.016
GPT teacher head0.254
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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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