Evidence map›Paper›PMID 33178943›Full record

ArticleBJR open2019

Positioning errors of metal localization devices with motion artifacts on kV and MV cone beam CT.

Teh Lin, Chang-Ming Charlie Ma

Open access · goldAbstract read
In one paragraph

Article in BJR open, 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
–field-weighted citation impact, top 98% 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, 1 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

2 authors at 2 institutions in 1 country.

Teh LinDepartment of Radiation Oncology Fox Chase Cancer Center, Temple University, Philadelphia, USA.
Chang-Ming Charlie MaDepartment of Radiation Oncology Fox Chase Cancer Center, Temple University, Philadelphia, USA.
Fox Chase Cancer Center · USTemple University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate motion artifacts on kV CBCT and MV CBCT images with metal localization devices for image-guided radiation therapy.

methodsThe 8 μ pelvis CBCT template for the Siemens Artiste MVision and Pelvis template for the Varian IX on-board Exact Arms kV were used to acquire CBCT images in this study. Images from both CBCT modalities were compared in CNRs, metal landmark absolute positions, and image volume distortion on three different planes of view. The images were taken on a breathing-simulated thoracic phantom in which several typical metal localization devices were implanted, including clips and wires for breast patients, gold seeds for prostate patients, and BBs as skin markers. To magnify the artifacts, a 4 cm diameter metal ball was also implanted into the thoracic phantom to mimic the metal artifacts.

resultsFor MV CBCT, the CNR at a 4 sec breathing cycle with 1 cm breathing amplitude was 5.0, 3.4 and 4.6 for clips, gold seeds and BBs, respectively while it was 1.5, 2.0 and 1.6 for the kV CBCT. On the images, the kV CBCT showed symmetric streaking artifacts both in the transverse and longitudinal directions relative to the motion direction. The kV CBCT images predicted 89 % of the expected volume, while the MV CBCT images predicted 95 % of the expected volume. The simulated soft tissue observed in the MVCT could not be detected in the kV CBCT.

conclusionThe MV CBCT images showed better volume prediction, less streaking effects and better CNRs of a moving metal target, ADVANCES IN KNOWLEDGE: This study would benefit clinicians to prescribe MV CBCT as localization modality for radiation treatment with moving target when metal markers are implanted.

Identifiers

PMID33178943
PMCPMC7592481
OpenAlexW2922430846

What OpenQuestion holds

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LicenceCC BY-NC
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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.