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Record W4405574614 · doi:10.1002/mp.17582

Feasibility of volumetric‐modulated arc therapy gating for cardiac radioablation using real‐time ECG signal acquisition and a dynamic phantom

2024· article· en· W4405574614 on OpenAlexaff
Cristiano Q. M. Reis, Jennifer M. Borsavage, Greg Berryhill, S Karnas, James L. Robar, Stewart Gaede

Bibliographic record

VenueMedical Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsWestern UniversityNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsTruebeamImaging phantomLinear particle acceleratorGatingSIGNAL (programming language)IsocenterMedicineNuclear medicineBeam (structure)Biomedical engineeringPhysicsComputer scienceOptics

Abstract

fetched live from OpenAlex

BACKGROUND: Stereotactic arrythmia radioablation (STAR) is a noninvasive technique to treat ventricular tachycardia (VT). Management of cardiorespiratory motion plays an essential role in VT-STAR treatments to improve treatment outcomes by reducing positional uncertainties and increasing dose conformality. Use of an electrocardiogram (ECG) signal, acquired in real-time, as a surrogate to gate the beam has the potential to fulfil that intent. PURPOSE: To investigate the gated delivery of volumetric-modulated arc therapy (VMAT) for STAR on a TrueBeam linear accelerator (linac) using a real-time acquired ECG signal and a dynamic cardiac phantom. METHODS AND MATERIALS: Dosimetric characteristics of a 6 MV flattening filter free (FFF) beam from a Varian TrueBeam linac were initially evaluated under high-frequency gating scenarios relevant to cardiac rhythms with respect to dose linearity, beam output, and energy quality. A microcontroller board was used to interface and gate the linac, sending a beam on/off signal. For real-time cardiac gated measurements, an AD8232 Heart Monitor board was used to acquire the ECG signal and synchronize the VMAT delivery to an ArcCHECK detector to a specific phase of the cardiac cycle. Gated dose distributions were compared against those acquired for a non-gated delivery mode. An in-house dynamic cardiac phantom was developed to simulate cardiorespiratory motion that correlates target position with the signal to gate the beam. Measured dose distributions using gafchromic film were also compared against the static (reference) mode in different scenarios with and without gating. RESULTS: ) between gated and non-gated modes were 0.91% and -0.44%, respectively. Comparison of delivered dose distributions for the VMAT plan without gating versus ECG synchronized gating modes provided a passing rate 98% for the gamma analysis with 1% relative dose difference, 1 mm distance-to-agreement criteria. For the synchronization of dose delivery with target position, passing rates were 98%, 97%, and 99% for the axial, coronal, and sagittal planes, respectively, when gating the beam based on target position for cardiac motion only, for 3%, 3 mm tolerance as compared to static mode. Without gating the beam, passing rates of the respective plans are 97%, 94%, and 99% for the cardiac motion only, and 67%, 57%, and 55% when including respiratory component of motion. CONCLUSION: A 6 MV-FFF TrueBeam is stable for performing gating in STAR under high-frequency gate windows within typical cardiac cycles. Agreement between measured dose distributions for a VMAT plan in static and ECG-synchronized deliveries and between static and target-position gated modes shows that the proposed methodology is feasible and can be implemented on a TrueBeam platform.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.017
GPT teacher head0.327
Teacher spread0.310 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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