Evidence map›Paper›PMID 36267969›Full record

ArticleFrontiers in oncology2022

Development and feasibility evaluation of an AR-assisted radiotherapy positioning system.

Gongsen Zhang, Xinchao Liu, Linlin Wang, Jian Zhu, Jinming Yu

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Augmented reality in brachytherapy: A narrative review.Journal of contemporary brachytherapy · 2024
    Review
  8. Article
  9. Article
  10. HoloLensTherapeutic advances in urology
    Review
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

5 authors.

Gongsen Zhang1Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Xinchao LiuCancer Center, Shandong University, Jinan, China.
Linlin Wang1Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jian Zhu1Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jinming Yu1Department of Radiology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The aim of this study is to develop an augmented reality (AR)-assisted radiotherapy positioning system based on HoloLens 2 and to evaluate the feasibility and accuracy of this method in the clinical environment. Methods: The obtained simulated computed tomography (CT) images of an "ISO cube", a cube phantom, and an anthropomorphic phantom were reconstructed into three-dimensional models and imported into the HoloLens 2. On the basis of the Vuforia marker attached to the "ISO cube" placed at the isocentric position of the linear accelerator, the correlation between the virtual and real space was established. First, the optimal conditions to minimize the deviation between virtual and real objects were explored under different conditions with a cube phantom. Then, the anthropomorphic phantom-based positioning was tested under the optimal conditions, and the positioning errors were evaluated with cone-beam CT. Results: Under the normal light intensity, the registration and tracking angles are 0°, the distance is 40 cm, and the deviation reached a minimum of 1.4 ± 0.3 mm. The program would not run without light. The hologram drift caused by the light change, camera occlusion, and head movement were 0.9 ± 0.7 mm, 1.0 ± 0.6 mm, and 1.5 ± 0.9 mm, respectively. The anthropomorphic phantom-based positioning errors were 3.1 ± 1.9 mm, 2.4 ± 2.5 mm, and 4.6 ± 2.8 mm in the X (lateral), Y (vertical), and Z (longitudinal) axes, respectively, and the angle deviation of Rtn was 0.26 ± 0.14°. Conclusion: The AR-assisted radiotherapy positioning based on HoloLens 2 is a feasible method with certain advantages, such as intuitive visual guidance, radiation-free position verification, and intelligent interaction. Hardware and software upgrades are expected to further improve accuracy and meet clinicalbrendaannmae requirements.

Indexed as

accuracyaugmented realityHoloLens 2image visualizationradiotherapy positioning

Identifiers

PMID36267969
PMCPMC9577500

What OpenQuestion holds

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LicenceCC BY
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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.