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Record W2030135423 · doi:10.1118/1.4884036

Novel, full 3D scintillation dosimetry using a static plenoptic camera

2014· article· en· W2030135423 on OpenAlexafffund
Mathieu Goulet, Madison Rilling, L Gingras, Sam Beddar, Luc Beaulieu, Louis Archambault

Bibliographic record

VenueMedical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMcGill UniversityHôtel-Dieu de QuébecUniversité du Québec à MontréalUniversité Laval
FundersEuropean Social FundNational Cancer InstituteNatural Sciences and Engineering Research Council of Canada
KeywordsDosimetryScintillationMedical imagingOpticsMedical physicsComputer graphics (images)Nuclear medicineComputer sciencePhysicsArtificial intelligenceMedicineDetector

Abstract

fetched live from OpenAlex

PURPOSE: Patient-specific quality assurance (QA) of dynamic radiotherapy delivery would gain from being performed using a 3D dosimeter. However, 3D dosimeters, such as gels, have many disadvantages limiting to quality assurance, such as tedious read-out procedures and poor reproducibility. The purpose of this work is to develop and validate a novel type of high resolution 3D dosimeter based on the real-time light acquisition of a plastic scintillator volume using a plenoptic camera. This dosimeter would allow for the QA of dynamic radiation therapy techniques such as intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT). METHODS: A Raytrix R5 plenoptic camera was used to image a 10 × 10 × 10 cm(3) EJ-260 plastic scintillator embedded inside an acrylic phantom at a rate of one acquisition per second. The scintillator volume was irradiated with both an IMRT and VMAT treatment plan on a Clinac iX linear accelerator. The 3D light distribution emitted by the scintillator volume was reconstructed at a 2 mm resolution in all dimensions by back-projecting the light collected by each pixel of the light-field camera using an iterative reconstruction algorithm. The latter was constrained by a beam's eye view projection of the incident dose acquired using the portal imager integrated with the linac and by physical consideration of the dose behavior as a function of depth in the phantom. RESULTS: The absolute dose difference between the reconstructed 3D dose and the expected dose calculated using the treatment planning software Pinnacle(3) was on average below 1.5% of the maximum dose for both integrated IMRT and VMAT deliveries, and below 3% for each individual IMRT incidences. Dose agreement between the reconstructed 3D dose and a radiochromic film acquisition in the same experimental phantom was on average within 2.1% and 1.2% of the maximum recorded dose for the IMRT and VMAT delivery, respectively. CONCLUSIONS: Using plenoptic camera technology, the authors were able to perform millimeter resolution, water-equivalent dosimetry of an IMRT and VMAT plan over a whole 3D volume. Since no moving parts are required in the dosimeter, the incident dose distribution can be acquired as a function of time, thus enabling the validation of static and dynamic radiation delivery with photons, electrons, and heavier ions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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 designSimulation or modeling
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

Citations51
Published2014
Admission routes2
Has abstractyes

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