Evidence map›Paper›PMID 42699179›Full record

ArticleReports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology2026

The smoothing factor in breast intensity-modulated radiotherapy: dosimetric impact and a predictive model of plan acceptability.

Tamás Ungvári, Döme Szabó, Ádám Gáldi, Amir Hossein Bassirani, Zsófia Dankovics, Balázs Kiss, Judit Olajos, Tibor Major, Károly Tőkési

Abstract read
In one paragraph

Article in Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

9 authors.

Tamás UngváriDepartment of Radiation Oncology, Markusovszky University Teaching Hospital, Szombathely, Hungary.ORCID https://orcid.org/0000-0002-9328-5935
Döme SzabóDepartment of Radiation Oncology, Markusovszky University Teaching Hospital, Szombathely, Hungary.
Ádám GáldiCenter of Radiotherapy, National Institute of Oncology, Budapest, Hungary.
Amir Hossein BassiraniDepartment of Radiation Oncology, Markusovszky University Teaching Hospital, Szombathely, Hungary.
Zsófia DankovicsDepartment of Radiation Oncology, Markusovszky University Teaching Hospital, Szombathely, Hungary.
Balázs KissDepartment of Radiation Oncology, Markusovszky University Teaching Hospital, Szombathely, Hungary.
Judit OlajosDepartment of Radiooncology, Jósa András Teaching Hospital, Nyíregyháza, Hungary.
Tibor MajorCenter of Radiotherapy, National Institute of Oncology, Budapest, Hungary.
Károly TőkésiLaboratory of Material Science, HUN-REN Institute for Nuclear Research, Debrecen, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The smoothing factor is a key planning parameter in intensity-modulated radiotherapy that affects both plan quality and deliverability. This study investigates the dosimetric impact of SF in breast radiotherapy and introduces a logistic regression-based model to predict plan acceptability. Materials and methods: IMRT plans were generated for 21 breast cancer patients using SF values from 10 to 300 (126 plans total). Dosimetric parameters included monitor units, ipsilateral lung dose (V Results: Plans with SF values between 100 and 150 provided the best compromise between monitor units, PTV coverage, and modulation complexity. The predictive model performed well (AUC = 0.88), with conformity index, maximum dose, and modulation complexity score emerging as the most influential predictors. It enables automated classification and supports smoothing factor selection. Conclusions: The smoothing factor strongly influences the performance of intensity-modulated radiotherapy plans. Our predictive model provides a robust tool for plan evaluation, supporting clinical decision-making and optimisation of smoothing factor in breast radiotherapy.

Indexed as

breast cancerintensity-modulated radiotherapy (IMRT)predictive modellingsmoothing factortreatment planning

Identifiers

PMID42699179
PMCPMC13544036

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Registered trials

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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.