Evidence map›Paper›PMID 34985188›Full record

ArticleJournal of applied clinical medical physics2022

Augmented reality-guided positioning system for radiotherapy patients.

Chunying Li, Zhengda Lu, Mu He, Jianfeng Sui, Tao Lin, Kai Xie, Jiawei Sun, Xinye Ni

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 19 citations in OpenAlex.

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  11. Brain Tumor and Augmented Reality: New Technologies for the Future.International journal of environmental research and public health · 2022
    Article
  12. Augmented reality-guided positioning system for radiotherapy patients.Journal of applied clinical medical physics · 2022
    Article
  13. 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

8 authors at 4 institutions in 1 country.

Chunying LiDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Zhengda LuDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Mu HeDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Jianfeng SuiDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Tao LinDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Kai XieDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Jiawei SunDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Xinye NiDepartment of Radiotherapy, Changzhou Second People's Hospital, Nanjing Medical University, Changzhou, China.
Changzhou University · CNChangzhou No.2 People's Hospital · CNNanjing Medical University · CNNanjing Jiangning Hospital · CN

Funding

Changzhou Key Laboratory of Medical Physics CM20193005Changzhou NO.2 People's Hospital 2021K009General Program of Jiangsu Provincial Health Commission M2020006Jiangsu Province postgraduate scientific research innovation plan in 2020 KYCX20_1421Science and Technology Programs for Young Talents of Changzhou Health Commission QN201932Young Talent Development Plan of Changzhou Health Commission CZQM2020067
6 · The paper itself

Abstract

In modern radiotherapy, error reduction in the patients' daily setup error is important for achieving accuracy. In our study, we proposed a new approach for the development of an assist system for the radiotherapy position setup by using augmented reality (AR). We aimed to improve the accuracy of the position setup of patients undergoing radiotherapy and to evaluate the error of the position setup of patients who were diagnosed with head and neck cancer, and that of patients diagnosed with chest and abdomen cancer. We acquired the patient's simulation CT data for the three-dimensional (3D) reconstruction of the external surface and organs. The AR tracking software detected the calibration module and loaded the 3D virtual model. The calibration module was aligned with the Linac isocenter by using room lasers. And then aligned the virtual cube with the calibration module to complete the calibration of the 3D virtual model and Linac isocenter. Then, the patient position setup was carried out, and point cloud registration was performed between the patient and the 3D virtual model, such the patient's posture was consistent with the 3D virtual model. Twenty patients diagnosed with head and neck cancer and 20 patients diagnosed with chest and abdomen cancer in the supine position setup were analyzed for the residual errors of the conventional laser and AR-guided position setup. Results show that for patients diagnosed with head and neck cancer, the difference between the two positioning methods was not statistically significant (P > 0.05). For patients diagnosed with chest and abdomen cancer, the residual errors of the two positioning methods in the superior and inferior direction and anterior and posterior direction were statistically significant (t = -5.80, -4.98, P < 0.05). The residual errors in the three rotation directions were statistically significant (t = -2.29 to -3.22, P < 0.05). The experimental results showed that the AR technology can effectively assist in the position setup of patients undergoing radiotherapy, significantly reduce the position setup errors in patients diagnosed with chest and abdomen cancer, and improve the accuracy of radiotherapy.

Indexed as

Augmented RealityHead and Neck NeoplasmsRadiation OncologyRadiotherapy, Image-GuidedCalibrationHumansPatient PositioningRadiotherapy Planning, Computer-AssistedRadiotherapy Setup Errorsaugmented realityposition setupposition setup errorradiation therapy

Identifiers

PMID34985188
PMCPMC8906221
OpenAlexW4206499328

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.