Evidence map›Paper›PMID 40065026›Full record

ArticleScientific reports2025

Adaptive calibration of Gafchromic EBT3 film using generalized additive neural networks.

Liyun Chang, Pang-Yu Chen, Shyh-An Yeh, Chen-Lin Kang, Chun-Ting Su, Tsair-Fwu Lee

Abstract read
PubMed Full text at PMC Publisher
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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. FilmQADose: Open-source software for radiochromic film dosimetry.Journal of applied clinical medical physics · 2026
    Article
  2. 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.

Liyun ChangDepartment of Medical Imaging and Radiological Sciences, I-Shou University, Kaohsiung, Taiwan, ROC. cliyun2000@gmail.com.
Pang-Yu ChenDepartment of Radiation Oncology, Sinlau Christian Hospital, Tainan, Taiwan, ROC. pangyuchen@yahoo.com.tw.
Shyh-An YehDepartment of Medical Imaging and Radiological Sciences, I-Shou University, Kaohsiung, Taiwan, ROC.
Chen-Lin KangDepartment of Radiation Oncology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan, ROC.
Chun-Ting SuDepartment of Medical Imaging and Radiological Sciences, I-Shou University, Kaohsiung, Taiwan, ROC.
Tsair-Fwu LeeMedical Physics and Informatics Laboratory of Electronics Engineering, National Kaohsiung University of Sciences and Technology, Kaohsiung, 80778, Taiwan, ROC. tflee@nkust.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In radiation therapy, precise dose distribution is essential for minimizing damage to normal tissues. Gafchromic EBT3 film is widely used to assure the quality of two-dimensional dosimetry but requires frequent recalibrations due to changes in sensitivity over time. This study presents a new calibration method using a Keras-based generalized additive neural network (GANN) to address film aging. EBT3 films from four lots were calibrated with a 6 MV photon beam and scanned on Epson scanners. The GANN method achieved percentage differences between calibrated and delivered doses within 5%, comparable to traditional recalibration methods, with an overall uncertainty of approximately 2%. It demonstrated improved stability and accuracy, significantly reducing the need for frequent recalibrations and providing a robust solution for long-term film dosimetry.

Indexed as

Film dose calibrationGafchromic filmNeural networkQuality assuranceRadiation dosimetry

Identifiers

PMID40065026
PMCPMC11894168

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.