Evidence map›Paper›PMID 29511688›Full record

ArticleBioMed research international2018

Optical Surface Management System for Patient Positioning in Interfractional Breast Cancer Radiotherapy.

Zhao Ma, Wei Zhang, Yi Su, Peiji Liu, Yinghua Pan, Gang Zhang, Yipeng Song

Abstract read
In one paragraph

Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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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

7 authors.

Zhao MaDepartment of Radiation Oncology, Yantai Yuhuangding Hospital, Yantai 264000, China.
Wei ZhangDepartment of Radiation Oncology, Yantai Yuhuangding Hospital, Yantai 264000, China.ORCID 0000-0001-9220-9167
Yi SuDepartment of Radiation Oncology, Yantai Yuhuangding Hospital, Yantai 264000, China.
Peiji LiuDepartment of Radiation Oncology, Yantai Yuhuangding Hospital, Yantai 264000, China.
Yinghua PanDepartment of Medical Imaging, Yantai Yuhuangding Hospital, Yantai 264000, China.
Gang ZhangDepartment of Medical Imaging, Yantai Yuhuangding Hospital, Yantai 264000, China.
Yipeng SongDepartment of Radiation Oncology, Yantai Yuhuangding Hospital, Yantai 264000, China.ORCID 0000-0002-8845-6939

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Optical Surface Management System (OSMS) is a simple, fast, reproducible, and accurate solution for patient set-up and can minimize random day-to-day set-up errors. However, studies in breast cancer patients are rare.

objectiveTo analyze 200 patient set-ups in 20 patients with breast cancer by comparing the OSMS with the conventional cone-beam computed tomography (CBCT).

methodDisplacements from concurrent OSMS and CBCT registrations were compared in a total of 200 setups of 20 patients to analyze the interfractional displacement and positioning displacement in three dimensions (lateral, longitudinal, and vertical directions).

resultsThe interfractional displacement on the lateral, longitudinal, and vertical directions for OSMS versus CBCT was 0.049 ± 0.254 versus 0.041 ± 0.244 centimeters (cm); 0.018 ± 0.261 versus 0.040 ± 0.242 cm; 0.062 ± 0.254 versus 0.065 ± 0.240 cm, respectively, without any significant difference (all

conclusionOSMS is an efficient tool to improve the accuracy and increase the speed for verifying the patient positioning in radiotherapy for breast cancer.

Indexed as

Patient PositioningRadiotherapy Planning, Computer-AssistedAdultBreastBreast NeoplasmsCone-Beam Computed TomographyFemaleHumansImage Processing, Computer-AssistedMiddle AgedPhantoms, ImagingRadiotherapy, Image-GuidedSurface Properties

Identifiers

PMID29511688
PMCPMC5817315

What OpenQuestion holds

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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.