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Record W4386188046 · doi:10.1002/mp.16674

Investigation of cyanine‐based infrared dyes as calibrants in radiochromic films

2023· article· en· W4386188046 on OpenAlexafffund
Rohith Kaiyum, Christopher W. Schruder, Ozzy Mermut, Alexandra Rink

Bibliographic record

VenueMedical Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoToronto Rehabilitation InstituteYork UniversityUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsMaterials scienceAbsorbanceDosimeterInfraredDosimetryCyanineAnalytical Chemistry (journal)Optical fiberIrradiationSubstrate (aquarium)OpticsRadiationChemistryFluorescence

Abstract

fetched live from OpenAlex

Abstract Background Radiochromic material such as lithium pentacosa‐10,12‐diynoate (LiPCDA) has been suggested as the radiation‐sensitive material for real‐time in vivo fiber‐optic dosimetry. In this configuration, micron‐thick radiochromic coating would measure the absorbed dose, where a major challenge is the uncertainty in the active material thickness, necessitating calibration. A homogeneously incorporated inert infrared (IR) dye, which must also be stable in ambient conditions and against radiolysis, can be added to the radiochromic film to enable optical calibration. Purpose This study investigates four commercial cyanine‐based dyes (IR‐783, IR‐806, IR‐868, and IR‐880) for use as an optical calibrant in fiber‐optic radiochromic dosimeters. Methods All dyes were dissolved in water to confirm solubility. IR‐783 and IR‐806 were dissolved in 10% w/w gelatin solution and coated onto a polyester substrate, which were then sandwiched between two layers of adhesives forming IR‐783 and IR‐806 films. A second batch of IR dyes in gelatin incorporated the LiPCDA, and was coated onto substrate and sandwiched between adhesive to form IR dye + LiPCDA films. The absorbance spectra of the films were measured periodically (176 and 102 days for IR‐dye films, and IR dye + LiPCDA, respectively). The average percentage absorbance, normalized to day 1, was fit to either a single or a double exponential decay model to calculate the spectral stability lifetime (τ1, τ2). Films were irradiated using a 6 MV LINAC beam with a standard setup of 100 source to axis distance (SAD), 10 cm × 10 cm field size and 1.5 cm depth. The change in absorbance of the IR‐dye + LiPCDA films were measured after they were irradiated to 1, 2, 5, 10, and 20 Gy at 3 Gy/min. Results Only IR‐783 and IR‐806 were sufficiently water soluble. In gelatin matrix, these dyes demonstrated a decrease in absorbance with time for IR‐783 and IR‐806 dyes, with IR‐783 films having an average τ1 = 73 ± 7 days and IR‐806 films τ1 = 7 ± 3 days. When combined with LiPCDA, IR‐806 degraded, losing its original peak at ∼820 nm. Similarly, IR‐783, combined with LiPCDA, showed signs of degradation; however, its original absorbance peak was still observed at ∼800 nm. In the IR‐783 + LiPCDA films, the IR‐783 dye had a τ = 4 ± 1 days, an order of magnitude faster than the IR‐783 with no LiPCDA films. When exposed to x‐ray irradiation, the IR‐783 dye in the IR‐783 + LiPCDA films showed no change in absorbance with increasing absorbed dose. In contrast, the LiPCDA in the films responded as expected, increasing in optical density with increased absorbed dose. Conclusions IR‐783 and IR‐806 dyes were observed to degrade over time following exponential decay curves. IR‐806 could not be combined with the LiPCDA without degrading. The combination of IR‐783 with LiPCDA demonstrated single exponential decay behavior at a comparatively faster rate than films that did not have LiPCDA. IR‐783 was insensitive to ionizing radiation and thus may be suitable for thickness correction, but an alternative manufacturing procedure may need to be developed.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.286
Teacher spread0.270 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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