Evidence map›Paper›PMID 40804590›Full record

ArticleMedical physics2025

Development and validation of a Monte Carlo model of a mobile accelerator for intraoperative radiation therapy.

Rafael Ayala, Álvaro Soza, María Jesús García, Rocío García, José Manuel Udías, Paula Ibáñez

Abstract readValidation Study
In one paragraph

Article in Medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Rafael AyalaServicio de Dosimetría y Radioprotección, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
Álvaro SozaServicio de Dosimetría y Radioprotección, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
María Jesús GarcíaServicio de Dosimetría y Radioprotección, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
Rocío GarcíaServicio de Dosimetría y Radioprotección, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
José Manuel UdíasNuclear Physics Group and IPARCOS, Department of Structure of Matter, Thermal Physics and Electronics, CEI Moncloa, Universidad Complutense de Madrid, Madrid, Spain.
Paula IbáñezNuclear Physics Group and IPARCOS, Department of Structure of Matter, Thermal Physics and Electronics, CEI Moncloa, Universidad Complutense de Madrid, Madrid, Spain.

Funding

Comunidad de Madrid (Community of Madrid) ASAP-CM-S2022/BMD7434European Union - RETIMAGER 101099096Spanish Government and Next Generation EU Recovery and Resilience Facility FLASHonCHIP-PLEC2022-009256Spanish Government and Next Generation EU Recovery and Resilience Facility INVENTOR-PID2022-137114OA-I00Spanish Government and Next Generation EU Recovery and Resilience Facility PROTOTWIN-TED2021-130592B-I00
6 · The paper itself

Abstract

backgroundIntraoperative electron radiation therapy (IOERT) relies on accurate and precise dose delivery to the tumor or tumor bed using mobile accelerators and interchangeable applicators, while critical organs are typically displaced or shielded during surgery. Treatment planning and linac commissioning are often based on water measurements, Monte Carlo (MC) simulations of the accelerator head and applicator system provide detailed insights into dose distributions and beam characteristics, offering additional support for clinical evaluation. PURPOSE: This study develops an MC model of the Liac HWL mobile accelerator using a hypothetical linac head geometry, due to the limited availability of detailed information on its internal components resulting from manufacturer disclosure policies. The model is optimized by adjusting three geometric parameters of the linac head and the initial beam energy spectrum to match experimental data. Additionally, it provides a set of Phase Space Files (PSFs) to support research and clinical applications.

methodsThe MC code PENELOPE, integrated with the penEasy framework, was used to simulate the Liac HWL. The hypothetical head geometry was defined by parameters such as the inner diameter of the head, the thickness of the scattering foil, and the thickness of the exit window. Output factors (OFs), percentage depth doses (PDDs), and off-axis ratios (OARs) were calculated in a virtual water phantom for different applicator sizes, bevel angles, and energies. Gamma analysis was employed to validate the model by comparing calculated and measured dose distributions. PSFs were made available in the IAEA PHSP format at four energies (6, 8, 10, and 12 MeV).

resultsThe model matched measured OFs within 2.5%. PDDs and OARs met the gamma analysis criteria (2% dose difference and 1 mm distance-to-agreement) in more than 93% of the studied cases, with the worst-case scenario occurring for the smallest applicator (3 cm diameter) with a 45° bevel angle at 6 MeV, resulting in OAR gamma passing rates of 85.7% at

conclusionsDespite the use of a hypothetical geometry, the model offers accurate dosimetric data and practical guidance for IOERT commissioning and treatment planning. It highlights potential dosimetric issues, particularly the lack of homogeneity in OARs for large-diameter applicators, and allows fine-tuning based on real-world data. Additionally, the PSFs generated in this study provide a reliable resource for simulating IORT dose distributions and analyzing the characteristics of IOERT beams.

Indexed as

Monte Carlo MethodParticle AcceleratorsRadiotherapyHumansIntraoperative PeriodRadiotherapy DosageRadiotherapy Planning, Computer-AssistedIOERTIORTLiac HWLMonte Carlo

Identifiers

PMID40804590
PMCPMC12350822

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.