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Record W4416391254 · doi:10.1016/j.pdpdt.2025.104874

Tissue optical properties correction of multispectral singlet oxygen luminescent dosimetry (MSOLD) for BPD-mediated Photodynamic Therapy

2025· article· en· W4416391254 on OpenAlexaff
Weibing Yang, Baozhu Lu, Madelyn Johnson, Hongjing Sun, Dennis Sourvanos, Brian C. Wilson, Robert H. Hadfield, Timothy C. Zhu

Bibliographic record

VenuePhotodiagnosis and Photodynamic Therapy · 2025
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSinglet oxygenDosimetryLuminescenceLaserMultispectral imageAbsorption (acoustics)Monte Carlo methodPhotodynamic therapySIGNAL (programming language)

Abstract

fetched live from OpenAlex

Significance Direct detection of singlet-state oxygen (¹O₂) is vital for type II PDT and achievable through multispectral singlet oxygen dosimetry (MSOLD). However, tissue scattering and absorption variations impact signal accuracy, necessitating correction factors. Approach A 690 nm CW laser (500 mW/cm²) excited Benzoporphyrin derivative (BPD) in methanol. The singlet oxygen spectrum was decomposed into ¹O₂ signal, BPD luminescence, and laser background using Singular Value Decomposition (SVD). Measurements were conducted in phantoms with varying optical properties: ink (= 0.1 – 1 cm⁻¹) and intralipid (= 5 – 40 cm⁻¹). Monte Carlo simulations validated the results. Results The ¹O₂ signal decreased nearly linearly with, while effects were influenced by detection fiber positioning. Experimental and simulated results showed strong agreement. Conclusions This study provides correction factors to enhance MSOLD accuracy under varying optical conditions, advancing its clinical application in PDT.

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 score0.056
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
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.309
Teacher spread0.288 · 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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