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Record W4389667456 · doi:10.1002/mp.16870

Performance characterization of a novel hybrid dosimetry insert for simultaneous spatial, temporal, and motion‐included dosimetry for MR‐linac

2023· article· en· W4389667456 on OpenAlexaff
Prescilla Uijtewaal, Pim Borman, B. M. Cote, Yoan LeChasseur, François Therriault‐Proulx, Rocco Flores, Stephanie Smith, Grant R. Koenig, Bas W. Raaymakers, Martin F. Fast

Bibliographic record

VenueMedical Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMarch of Dimes Canada
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsImaging phantomMultileaf collimatorDosimeterDosimetryLinear particle acceleratorScannerScintillatorPhysicsNuclear medicineOpticsMedical physicsCollimated lightCollimatorMatch movingMaterials scienceDetectorBeam (structure)MedicineMotion (physics)

Abstract

fetched live from OpenAlex

Abstract Background Several (online) adaptive radiotherapy procedures are available to maximize healthy tissue sparing in the presence of inter/intrafractional motion during stereotactic body radiotherapy (SBRT) on an MR‐linac. The increased treatment complexity and the motion‐delivery interplay during these treatments require MR‐compatible motion phantoms with time‐resolved dosimeters to validate end‐to‐end workflows. This is not possible with currently available phantoms. Purpose Here, we demonstrate a new commercial hybrid film‐scintillator cassette, combining high spatial resolution radiochromic film with four time‐resolved plastic scintillator dosimeters (PSDs) in an MRI‐compatible motion phantom. Methods First, the PSD's performance for consistency, dose linearity, and pulse repetition frequency (PRF) dependence was evaluated using an RW3 solid water slab phantom. We then demonstrated the MRI4D scintillator cassette's suitability for time‐resolved and motion‐included quality assurance for adapt‐to‐shape (ATS), trailing, gating, and multileaf collimator (MLC) tracking adaptations on a 1.5 T MR‐linac. To do this, the cassette was inserted into the Quasar MRI4D phantom, which we used statically or programmed with artificial and patient‐derived motion. Simultaneously with dose measurements, the beam‐gating latency was estimated from the time difference between the target entering/leaving the gating window and the beam‐on/off times derived from the time‐resolved dose measurements. Results Experiments revealed excellent detector consistency (standard deviation 0.6%), dose linearity (R2 = 1), and only very low PRF dependence (0.4%). The dosimetry cassette demonstrated a near‐perfect agreement during an ATS workflow between the time‐resolved PSD and treatment planning system (TPS) dose (0%–2%). The high spatial resolution film measurements confirmed this with a 1%/1‐mm local gamma pass‐rate of 90%. When trailing patient‐derived prostate motion for a prostate SBRT delivery, the time‐resolved cassette measurements demonstrated how trailing mitigated the motion‐induced dose reductions from 1%–17% to 1%–2% compared to TPS dose. The cassette's simultaneously measured spatial dose distribution highlighted the dosimetric gain of trailing by improving the 3%/3‐mm local gamma pass‐rates from 80% to 97% compared to the static dose. Similarly, the cassette demonstrated the benefit of real‐time adaptations when compensating patient‐derived respiratory motion by showing how the TPS dose was restored from 2%–56% to 0%–12% (gating) and 1%–26% to 1%–7% (MLC tracking) differences. Larger differences are explainable by TPS‐PSD coregistration uncertainty combined with a steep dose gradient outside the PTV. The cassette also demonstrated how the spatial dose distributions were drastically improved by the real‐time adaptations with 1%/1‐mm local gamma pass‐rates that were increased from 8 to 79% (gating) and from 35 to 89% (MLC tracking). The cassette‐determined beam‐gating latency agreed within 12 ms with the ground truth latency measurement. Film and PSD dose agreed well for most cases (differences relative to TPS dose 4%), while film‐PSD coregistration uncertainty caused relative differences of 5%–8%. Conclusions This study demonstrates the excellent suitability of a new commercial hybrid film‐scintillator cassette for simultaneous spatial, temporal, and motion‐included dosimetry.

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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)0.001
metaresearch head score (Gemma)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.285
Teacher spread0.271 · 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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Citations8
Published2023
Admission routes1
Has abstractyes

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