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Record W4412464003 · doi:10.1002/mp.17900

Exploring the potential of Raman micro‐spectroscopy of radiochromic films for experimental microdosimetry

2025· article· en· W4412464003 on OpenAlexafffund
Connor McNairn, Kirsty Milligan, Iymad Mansour, Edana Cassol, Vinita Chauhan, Jeffrey L. Andrews, Sanjeena Subedi, Andrew Jirasek, Bryan Muir, Rowan M. Thomson, Sangeeta Murugkar

Bibliographic record

VenueMedical Physics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsNational Research Council CanadaHealth CanadaPrincess Margaret Cancer CentreUniversity of British Columbia, Okanagan CampusMétis National CouncilUniversity of TorontoCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsRaman spectroscopyMaterials scienceDosimetryMicroscopeOpticsMicroscopyReproducibilityMicrometerNuclear medicineChemistryPhysics

Abstract

fetched live from OpenAlex

Background Micrometer‐scale dosimetry is crucial when estimating the energy deposited within micrometer‐scale biological targets exposed to low doses or high dose gradients. Raman micro‐spectroscopy read‐out of radiochromic films (RCFs) permits micrometer‐scale resolution; this presents a novel opportunity to explore its feasibility for experimental microdosimetry. Purpose The purpose of this work was to develop a novel approach towards generating data for experimental microdosimetry. The objective was to develop a method based on high (1–2 µm) spatial resolution Raman micro‐spectroscopy of RCFs, ensuring reproducibility of data while producing two‐dimensional intensity maps of the Raman response. Methods EBT3 RCFs were irradiated to doses between 0.2 Gy and 2 Gy using a clinical linear accelerator. Raman spectra were collected using a custom Raman microscope fitted with 40× and 60× water immersion (WI) objectives, and a commercial Raman microscope utilizing a 100× dry objective. The excitation source of the custom setup was circularly polarized to minimize the influence of polarization on the film read‐out. The Raman response of the RCFs was measured over a 100 × 100 µm 2 region of interest (ROI) with a 10 × 10 grid. The Raman response of the active layer of the film was normalized to the radiation‐insensitive monomer peak at 2260 cm −1 . The Raman intensities of the 1445 cm −1 and 2060 cm −1 peaks were used to generate dose response curves for each microscope setup. Maps of the Raman intensity over the 100 × 100 µm 2 ROI for the 60× WI setup were used to quantify the heterogeneity in the film response. Higher resolution point‐scans were performed over a 20 × 20 µm 2 ROI for 0 Gy and 2 Gy samples. Results The dose response of each Raman microscope setup over the 0–2 Gy dose range was linear ( r 2 of 0.98) after normalization to the 2260 cm −1 Raman peak in the active layer. The slope of the dose response curve of the commercial microscope exhibited dependence on the film orientation; this was minimized with the custom Raman setup by using the circularly polarized excitation source. The relative standard deviation (RSD) of the 1445 cm −1 peak Raman intensity over the 100 × 100 µm 2 ROIs was significant (∼11%) for each microscope setup, and independent of dose. The Raman intensity distribution maps revealed that the heterogeneity in Raman response across the ROI was on the same size‐scale (1.62 µm × 9.4 µm) of the lithium salt of pentacosa‐10,12‐diynoic acid (LiPCDA) crystals comprising the active layer of the film. Conclusions This work explored the feasibility of a Raman micro‐spectroscopy‐based read‐out technique of RCFs for experimental microdosimetry. Utilizing the 2260 cm −1 peak in the Raman spectrum as an internal standard for normalization produced a linear ( r 2 of 0.98) dose‐response curve in the 0–2 Gy dose range. Utilizing circularly polarized laser excitation minimized the polarization dependence of the film and increased the reproducibility of the Raman measurements. Spatial heterogeneity in the concentration of PCDA crystals in the active layer was visualized based on two‐dimensional maps of the Raman intensity response to explore the implications on microdosimetry.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.012

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.015
GPT teacher head0.303
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 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".

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Citations2
Published2025
Admission routes2
Has abstractyes

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