Evidence map›Paper›PMID 37720460›Full record

ArticlePhysics and imaging in radiation oncology2023

Geometric accuracy in patient positioning for stereotactic radiotherapy of intracranial tumors.

Jan-Hendrik Bolten, Jürgen Dunst, Frank-André Siebert

Abstract read
In one paragraph

Article in Physics and imaging in radiation oncology, 2023. 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

3 authors.

Jan-Hendrik BoltenClinic of Radiotherapy (Radiooncology), University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany.
Jürgen DunstClinic of Radiotherapy (Radiooncology), University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany.
Frank-André SiebertClinic of Radiotherapy (Radiooncology), University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/Purpose: This study determines and compares the geometric setup errors between stereoscopic x-ray and kilo-voltage cone beam CT (CBCT) in phantom tests on a linear accelerator (linac) for image-guided (IG) stereotactic radiotherapy of intracranial tumors. Additionally, dose-volume metrics in the target volumes of the setup errors of CBCT were evaluated. Materials/Methods: A Winston-Lutz- and an anthropomorphic phantom were used. The mean deviation and root mean square error (RMSE) of CBCT and stereoscopic x-ray were compared. Dose-volume metrics of the planning target volume (PTV) and gross target volume (GTV) for CBCT were calculated. Results: The RMSEs in the tests with the Winston-Lutz-Phantom were 0.3 mm, 1.1 mm and 0.3 mm for CBCT and 0.1 mm, 0,1 mm and <0.1 mm for stereoscopic x-ray in the translational dimensions (right-left, anterior-posterior and superior-inferior). The RMSEs in the tests with the anthropomorphic phantom were 0.3 mm, 0.2 mm and 0.1 mm for CBCT and 0.1 mm, 0,1 mm and <0.1 mm for stereoscopic x-ray. The effects on dose-volume metrics of the setup errors of CBCT on the GTV were within 1 % for all considered dose values. The effects on the PTV were within 5 % for all considered dose values. Conclusion: Both IG systems provide high accuracy patient positioning within a submillimeter range. The phantom tests exposed a slightly higher accuracy of stereoscopic x-ray than CBCT. The comparison with other studies with a similar purpose emphasizes the importance of individual IG installation quality assurance.

Indexed as

Accuracy in patient positioningCBCTExacTracImage-guided radiotherapyIntracranial tumorsStereotactic Radiotherapy

Identifiers

PMID37720460
PMCPMC10500024

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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.