Evidence map›Paper›PMID 29544504›Full record

ArticleRadiation oncology (London, England)2018

In silico assessment of the dosimetric quality of a novel, automated radiation treatment planning strategy for linac-based radiosurgery of multiple brain metastases and a comparison with robotic methods.

Krzysztof Slosarek, Barbara Bekman, Jacek Wendykier, Aleksandra Grządziel, Antonella Fogliata, Luca Cozzi

Abstract readComparative Study
In one paragraph

Article in Radiation oncology (London, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Clinical implementation of HyperArc.Physical and engineering sciences in medicine · 2022
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  19. Recent developments in non-coplanar radiotherapy.The British journal of radiology · 2019
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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.

Krzysztof SlosarekDepartment of Radiotherapy Planning, Maria Sklodowska Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
Barbara BekmanDepartment of Radiotherapy Planning, Maria Sklodowska Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
Jacek WendykierDepartment of Radiotherapy Planning, Maria Sklodowska Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
Aleksandra GrządzielDepartment of Radiotherapy Planning, Maria Sklodowska Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.
Antonella FogliataRadiotherapy and Radiosurgery Department, Humanitas Clinical and Research Hospital, Rozzano, Italy.
Luca CozziRadiotherapy and Radiosurgery Department, Humanitas Clinical and Research Hospital, Rozzano, Italy. luca.cozzi@humanitas.it.ORCID http://orcid.org/0000-0001-7862-898X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo appraise the dosimetric features and the quality of the treatment plan for radiosurgery of multiple brain metastases optimized with a novel automated engine and to compare with plans optimized for robotic-based delivery.

methodsA set of 15 patients with multiple brain metastases was selected for this in silico study. The technique under investigation is the recently introduced HyperArc. For all patients, three treatment plans were computed and compared: i: a HyperArc; ii: a standard VMAT; iii) a CyberKnife. Dosimetric features were computed for the clinical target volumes as well as for the healthy brain tissue and the organs at risk.

resultsThe data showed that the best dose homogeneity was achieved with the VMAT technique. HyperArc allowed to minimize the volume of brain receiving 4Gy (as well as for the mean dose and the volume receiving 12Gy, although not statistically significant). The smallest dose on 1 cm

conclusionAt treatment planning level, the study demonstrates that the use of HyperArc technique can significantly improve the sparing of the healthy brain while maintaining a full coverage of the target volumes.

Indexed as

Brain NeoplasmsHumansRadiometryRadiosurgeryRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRetrospective StudiesRoboticsCyberKnifeHyperArcMultiple brain metastasesRadiosurgeryVMAT

Identifiers

PMID29544504
PMCPMC5856310

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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.