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Record W2942777861 · doi:10.1002/mp.13414

Cherenkov emission‐based external radiotherapy dosimetry: I. Formalism and feasibility

2019· article· en· W2942777861 on OpenAlexafffund
Yana Zlateva, Bryan Muir, Issam El Naqa, Jan Seuntjens

Bibliographic record

VenueMedical Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsNational Research Council CanadaMcGill University
FundersFonds de recherche du Québec – Nature et technologiesMcGill University Health CentreNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsDosimetryPhysicsDetectorCherenkov radiationDosimeterTruebeamMonte Carlo methodElectronOpticsComputational physicsPhotonCharged particleFormalism (music)Beam (structure)RadiationNuclear physicsLinear particle acceleratorNuclear medicineIon

Abstract

fetched live from OpenAlex

Purpose Cherenkov emission (CE)‐based external beam dosimetry is envisioned to involve the detection of CE directly in water with placement of a high‐resolution detector out of the field, avoiding perturbations encountered with traditional dosimeters. In this work, we lay out the groundwork for its implementation in the clinic and motivate CE‐based dosimeter design efforts. To that end, we examine a formalism for broad‐beam in‐water CE‐based dosimetry of external radiotherapy beams, design and test a Monte Carlo (MC) simulation framework for the calculation of CE‐to‐dose conversion factors used by the formalism, and demonstrate the experimental feasibility of this method. Methods The formalism is conceptually analogous to ionization‐based dosimetry and employs CE‐to‐dose conversion factors, , including only and all CE generated within polar anglesθ ± δθon beam axis. The EGSnrc user code SPRRZnrc is modified to calculate , as well as CE spectral and angular distributions. The modified code is tested with monoenergetic parallel electrons on a thin water slab. Detector configurations are examined for broad 6–22 MeV electron beams from a BEAMnrc TrueBeam model, with a focus on (4π detection), , and ( is the CE angle of relativistic electrons in water). We perform a relative experimental validation at with electron beams, using a simple detector design with spherical optics and geometrical optics approximation of the sensitive volume, which spans the water tank. Due to transient charged particle equilibrium, broad photon beams are generally less sensitive to beam quality, depth, and angle. Results For 0.1–50 MeV electrons on a thin water slab, the code outputs CE photon spectral density per unit mass (calculated from dose and ) and angle in agreement with theory within ±0.03% and , respectively, corresponding to the output precision. The configuration was found impractical due to detection considerations. Detection at for small δθexhibited beam quality dependence of the same order as well as strong superficial depth dependence. A 4π configuration ameliorates these effects. A more practical approach may employ a large numerical aperture. In comparing with literature, we find that these effects are less pronounced for broad photon beams in water, as expected. Measured relative at small δθwere within 1% of simulated factors (relative to their local average) for percent‐depth CE (PDC) >50%. At other depths, deviations were in accordance with signal‐to‐noise, known detector limitations, and approximations. It was found that the CE spectrum is beam quality and depth invariant, while for electron beams the CE angular distribution is strongly dependent on beam quality and depth. However, the uncertainty of CE and PDC measurement at detection for small δθdue to deviations around δθwas shown to be ≤1% and <0.1% (k = 1), respectively. The robustness to expected detector setup variations was found to result in ≤1% (k = 1) local uncertainty contribution for PDC >50%. Conclusions Based on our MC and experimental studies, we conclude that the CE‐based method is promising for high‐resolution, perturbation‐free, three‐dimensional dosimetry in water, with specific applications contingent on comprehensive detector development and characterization.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
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)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.002
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 head0.013
GPT teacher head0.306
Teacher spread0.293 · 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 designTheoretical or conceptual
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".

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Citations23
Published2019
Admission routes2
Has abstractyes

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