Evidence map›Paper›PMID 30808377›Full record

ArticleRadiation oncology (London, England)2019

Comparison of gamma index based on dosimetric error and clinically relevant dose-volume index based on three-dimensional dose prediction in breast intensity-modulated radiation therapy.

Akari Kaneko, Iori Sumida, Hirokazu Mizuno, Fumiaki Isohashi, Osamu Suzuki, Yuji Seo, Keisuke Otani, Keisuke Tamari, Kazuhiko Ogawa

Open access · goldAbstract readComparative Study
In one paragraph

Article in Radiation oncology (London, England), 2019. 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
0.6field-weighted citation impact, top 32% of its field
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, 4 citations in OpenAlex.

  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

9 authors at 2 institutions in 1 country.

Akari KanekoDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan. a.kaneko@radonc.med.osaka-u.ac.jp.
Iori SumidaDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Hirokazu MizunoDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Fumiaki IsohashiDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Osamu SuzukiDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Yuji SeoDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Keisuke OtaniDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Keisuke TamariDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Kazuhiko OgawaDepartment of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, 565-0871, Osaka, Japan.
Osaka University · JPSuita Tokushukai Hospital · JP

Funding

JSPS KAKENHI 15K09995
6 · The paper itself

Abstract

backgroundMeasurement-guided dose reconstruction has lately attracted significant attention because it can predict the delivered patient dose distribution. Although the treatment planning system (TPS) uses sophisticated algorithm to calculate the dose distribution, the calculation accuracy depends on the particular TPS used. This study aimed to investigate the relationship between the gamma passing rate (GPR) and the clinically relevant dose-volume index based on the predicted 3D patient dose distribution derived from two TPSs (XiO, RayStation).

methodsTwenty-one breast intensity-modulated radiation therapy plans were inversely optimized using XiO. With the same plans, both TPSs calculated the planned dose distribution. We conducted per-beam measurements on the coronal plane using a 2D array detector and analyzed the difference in 2D GPRs between the measured and planned doses by commercial software. Using in-house software, we calculated the predicted 3D patient dose distribution and derived the predicted 3D GPR, the predicted per-organ 3D GPR, and the predicted clinically relevant dose-volume indices [dose-volume histogram metrics and the value of the tumor-control probability/normal tissue complication probability of the planning target volume and organs at risk]. The results derived from XiO were compared with those from RayStation.

resultsWhile the mean 2D GPRs derived from both TPSs were 98.1% (XiO) and 100% (RayStation), the mean predicted 3D GPRs of ipsilateral lung (73.3% [XiO] and 85.9% [RayStation]; p < 0.001) had no correlation with 2D GPRs under the 3% global/3 mm criterion. Besides, this significant difference in terms of referenced TPS between XiO and RayStation could be explained by the fact that the error of predicted V

conclusionsGPR is useful as a patient quality assurance to detect dosimetric errors; however, it does not necessarily contain detailed information on errors. Using the predicted clinically relevant dose-volume indices, the clinical interpretation of dosimetric errors can be obtained. We conclude that a clinically relevant dose-volume index based on the predicted 3D patient dose distribution could add to the clinical and biological considerations in the GPR, if we can guarantee the dose calculation accuracy of referenced TPS.

Indexed as

AlgorithmsBreast NeoplasmsFemaleGamma RaysHumansRadiation DosageRadiometryRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedSoftware

Identifiers

PMID30808377
PMCPMC6390354
OpenAlexW2943128246

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LicenceCC BY
Read underepoch 390

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.