MétaCan
Menu
Back to cohort
Record W4417417344 · doi:10.1117/1.jbo.30.s3.s34115

Comparison of multispectral singlet oxygen luminescence dosimetry and singlet oxygen explicit dosimetry in artificial phantom

2025· article· en· W4417417344 on OpenAlexaff
Weibing Yang, Baozhu Lu, Madelyn Johnson, Dennis Sourvanos, Hongjing Sun, Andreea Dimofte, Vikas Vikas, Robert H. Hadfield, Brian C. Wilson, Timothy C. Zhu

Bibliographic record

VenueJournal of Biomedical Optics · 2025
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity Health Network
FundersNational Institute of Dental and Craniofacial ResearchNational Institutes of HealthUniversity of Pennsylvania
KeywordsSinglet oxygenDosimetryLuminescencePhotosensitizerImaging phantomFluenceMultispectral imageSinglet state

Abstract

fetched live from OpenAlex

SignificanceDirect detection of singlet-state oxygen (O12) is a critical objective in Type II photodynamic therapy (PDT) due to its pivotal role in mediating therapeutic effects. Although multispectral singlet oxygen dosimetry (MSOLD) has demonstrated the capability to detect O12 luminescence both in vitro and in vivo, there remains no standardized method for accurately quantifying reactive singlet oxygen, [O2]rx1, based on these measured signals. By contrast, the singlet oxygen explicit dosimetry (SOED) model offers a robust framework for calculating [O2]rx1. Demonstrating that O12 luminescence obtained through MSOLD can reliably quantify [O2]rx1, as achieved by the SOED model, is essential for advancing the accuracy and applicability of PDT dosimetry.AimWe aim to evaluate the accuracy and reliability of MSOLD in quantifying O12 concentrations from measured O12 luminescence in benzoporphyrin derivative (BPD)-mediated PDT. The performance of MSOLD is assessed by comparing its results with those derived from the SOED model.ApproachA continuous-wave 690 nm laser was used to excite a nanoparticle formulation of BPD, tradename Visudyne® in methanol at varying concentrations (2 to 6 mg/L). The singlet oxygen luminescence was measured using an InGaAs spectrometer and analyzed using a singular value decomposition algorithm. Near-infrared singlet oxygen emission at ∼1270 nm was extracted as O12 luminescence. Real-time singlet oxygen spectra were collected over 900 s using a 1.5 mm diameter fiber optic. Ground-state oxygen concentration was measured with a commercial oxygen probe, photosensitizer concentration was determined with a custom-made contact probe, and photon fluence rate was assessed with an isotropic detector. [O2]rx1 was then calculated based on the SOED model.ResultsThe extracted singlet oxygen (O12) luminescence exhibited clear concentration-dependent trends, with higher BPD concentrations producing stronger O12 luminescence. Over time, the O12 luminescence decayed due to photosensitizer bleaching. In addition, a strong linear correlation was observed between the O12 luminescence measured via MSOLD and the reactive oxygen species (ROS) concentrations calculated using the SOED model. We also investigated the impact of tissue optical properties on singlet oxygen luminescence detection and developed correction factors to account for their variations.ConclusionsWe demonstrate that singlet oxygen (O12) detected through MSOLD can reliably quantify ROS concentrations in BPD-mediated PDT with accuracy comparable to the SOED model, which requires separate measurements of light fluence rate, photosensitizer concentration, and oxygen availability, followed by modeling to estimate the amount of reactive singlet oxygen. By contrast, MSOLD can also be a more cost-effective, simpler, and faster alternative to SOED as it directly measures the singlet oxygen luminescence to quantify reactive singlet oxygen. Under appropriate correction for tissue optical properties, MSOLD presents a promising, robust, and direct dosimetry solution for clinical PDT applications.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.284
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
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 head0.029
GPT teacher head0.382
Teacher spread0.353 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biomedical OpticsSame topicPhotodynamic Therapy Research StudiesFrench-language works237,207