Evidence map›Paper›PMID 41354671›Full record

ArticleScientific reports2025

A GEANT4 Monte Carlo simulation study for the computation of output factors and out-of-field dosimetry in breast IOERT.

Sara Savatović, Licia Toscano, Mara Severgnini, Francesco Longo

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sara SavatovićResearch Group Biomedical Imaging Physics, Department of Physics, TUM School of Natural Sciences & Munich Institute of Biomedical Engineering, Technical University of Munich, 85748, Garching, Germany. sara.savatovic@tum.de.
Licia ToscanoCRO Aviano, National Cancer Institute, IRCCS, 33081, Aviano, Italy.
Mara SevergniniDepartment of Medical Physics, Azienda Sanitaria Universitaria Giuliano-Isontina (ASUGI), 34129, Trieste, Italy.
Francesco LongoDepartment of Physics, University of Trieste, 34127, Trieste, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The goal of breast Intraoperative Electron Radiation Therapy (IOERT) is to deliver a uniform single fraction dose of 10-25 Gy to a surgically exposed volume of tissue at risk (tumor bed) while minimizing exposure to surrounding healthy tissue, with the patient under anesthesia. Currently, all the necessary information for the geometric and physical treatment arrangement is collected during the commissioning phase, when a preliminary dosimetric characterization of the accelerator is performed for clinical use in accordance with international protocols. During this process, output factors (OFs)-correction factors that account for dose differences relative to the reference condition-are measured. Therefore, since treatment plans rely exclusively on the OF and experimental measurements can be affected by large errors (on the order of 30%), a tuned Monte Carlo model provides a valuable tool for treatment validation. It is particularly valuable for evaluating quantities that are difficult to measure directly, such as dose variations resulting from shielding disk misalignment (to protect underlying healthy tissue) or out-of-field exposure to organs at risk in complex clinical scenarios (e.g., patients with implantable electronic devices or during pregnancy).

Indexed as

Breast NeoplasmsElectronsMonte Carlo MethodRadiometryRadiotherapy Planning, Computer-AssistedBreastComputer SimulationFemaleHumansRadiotherapy Dosage3D dosimetryGEANT4IOERTMC simulationMobetron1000Output factor

Identifiers

PMID41354671
PMCPMC12686418

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.