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Application of volumetric modulated arc therapy (VMAT) for craniospinal irradiation: Dosimetric analysis and clinical implementation

2025· article· en· W4410635774 on OpenAlexaff
Pham Nguyen Tuong, Phan Canh Duy, Nguyen Van Thanh, Lich Nguyen, Mai Thi Thao, Dương Thanh Tài, Peter Sandwall, Sarah Ashmeg, Abdelmoneim Sulieman, James C. L. Chow

Bibliographic record

VenueRadiation Physics and Chemistry · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersPrincess Nourah Bint Abdulrahman University
KeywordsNuclear medicineArc (geometry)Radiation therapyMedicineMedical physicsRadiologyMathematics

Abstract

fetched live from OpenAlex

: Craniospinal irradiation (CSI) is crucial for treating central nervous system malignancies like medulloblastoma and high-risk brain tumors with meningeal spread potential. Traditional 3D-conformal radiotherapy (3D-CRT) requires multiple field junctions, increasing the risks of dose inhomogeneity and unnecessary exposure to healthy tissues. This study investigates the use of VMAT on an Elekta Synergy linear accelerator with 160 leaf Agility multi-leaf collimator at the Hue Central Hospital, Vietnam. Five pediatric patients were treated using VMAT with a prescribed dose of 23.4 Gy in 13 fractions. Immobilization was achieved using vacuum bags and thermoplastic masks in a supine position. Planning CT scans were performed with 3-mm slice thickness, and treatment plans were created using the Monaco treatment planning system, v6.1.4.0. VMAT plans incorporated two isocenters with overlapping arcs to ensure comprehensive craniospinal coverage. Key parameters, including conformity index (CI), homogeneity index (HI), monitor units (MU), and dose to organs-at-risk (OARs), were analyzed. Mechanical and positional uncertainties, including simulated ±3 mm patient shifts, were also evaluated. The planning target volume (PTV) achieved exceptional coverage, with V95% averaging 99.27 ± 0.52% and hotspot volumes (V107% and V110%) minimized to 1.96 ± 0.39% and 0.05 ± 0.07%, respectively. The CI and HI averaged 0.93 ± 0.02 and 1.06 ± 0.01, indicating outstanding plan quality and dose uniformity. OAR doses, including those for critical structures like the lenses, lungs, heart, and kidneys, adhered to planning constraints, minimizing potential long-term side effects. Treatment efficiency was demonstrated with an average MU of 1197.56 ± 88.49, showcasing the practicality of the approach. This study demonstrates the successful implementation of VMAT for CSI on the Elekta Synergy system. The results highlight excellent PTV coverage, minimal hotspot volumes, and high plan quality with optimal conformity and homogeneity indices. Doses to OARs remained within safe limits, minimizing potential adverse effects.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.626
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.342
Teacher spread0.335 · 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 designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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