Evidence map›Paper›PMID 39090719›Full record

ArticleArthroplasty (London, England)2024

Application of image recognition-based tracker-less augmented reality navigation system in a series of sawbone trials.

Elvis Chun-Sing Chui, Kyle Ka-Kwan Mak, Randy Hin-Ting Ng, Ericsson Chun-Hai Fung, Harold Hei-Ka Mak, Mei-Shuen Chan, Wei Zhao, Xiuyun Su, Jin Zhang, Jianglong Xu and 7 more

Abstract read
In one paragraph

Article in Arthroplasty (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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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

17 authors.

Elvis Chun-Sing ChuiDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. elvis_chui@cuhk.edu.hk.
Kyle Ka-Kwan MakDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Randy Hin-Ting NgDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Ericsson Chun-Hai FungDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Harold Hei-Ka MakDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Mei-Shuen ChanDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Wei ZhaoDepartment of Orthopaedics, Southern University of Science and Technology Hospital, Shenzhen, 518055, China.
Xiuyun SuDepartment of Orthopaedics, Southern University of Science and Technology Hospital, Shenzhen, 518055, China.
Jin ZhangDepartment of Orthopaedics, Shenzhen Hospital of Southern Medical University, Shenzhen, 510086, China.
Jianglong XuDepartment of Orthopaedics, Shenzhen Children's Hospital, Shenzhen, 518026, China.
Hongxun SangDepartment of Orthopaedics, Shenzhen Hospital of Southern Medical University, Shenzhen, 510086, China.
Guoxian PeiDepartment of Orthopaedics, Southern University of Science and Technology Hospital, Shenzhen, 518055, China.
Michael Tim-Yun OngDepartment of Orthopaedics and Traumatology, Prince of Wales Hospital, Shatin, Hong Kong SAR, China.
Wing-Hoi CheungDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Sheung-Wai LawDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Ronald Man Yeung WongDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Patrick Shu-Hang YungDepartment of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.

Funding

Innovation and Technology Fund GHP/100/21SZInnovation and Technology Fund GHP/180/20SZInnovation and Technology Fund ITSP Tier3 (ITS/172/16))Innovation and Technology Fund PRP/027/20FX
6 · The paper itself

Abstract

backgroundThis study introduced an Augmented Reality (AR) navigation system to address limitations in conventional high tibial osteotomy (HTO). The objective was to enhance precision and efficiency in HTO procedures, overcoming challenges such as inconsistent postoperative alignment and potential neurovascular damage.

methodsThe AR-MR (Mixed Reality) navigation system, comprising HoloLens, Unity Engine, and Vuforia software, was employed for pre-clinical trials using tibial sawbone models. CT images generated 3D anatomical models, projected via HoloLens, allowing surgeons to interact through intuitive hand gestures. The critical procedure of target tracking, essential for aligning virtual and real objects, was facilitated by Vuforia's feature detection algorithm.

resultsIn trials, the AR-MR system demonstrated significant reductions in both preoperative planning and intraoperative times compared to conventional navigation and metal 3D-printed surgical guides. The AR system, while exhibiting lower accuracy, exhibited efficiency, making it a promising option for HTO procedures. The preoperative planning time for the AR system was notably shorter (4 min) compared to conventional navigation (30.5 min) and metal guides (75.5 min). Intraoperative time for AR lasted 8.5 min, considerably faster than that of conventional navigation (31.5 min) and metal guides (10.5 min).

conclusionsThe AR navigation system presents a transformative approach to HTO, offering a trade-off between accuracy and efficiency. Ongoing improvements, such as the incorporation of two-stage registration and pointing devices, could further enhance precision. While the system may be less accurate, its efficiency renders it a potential breakthrough in orthopedic surgery, particularly for reducing unnecessary harm and streamlining surgical procedures.

Indexed as

Augmented realityComputer-assisted navigation systemComputer-assisted surgeryMixed realitySurgical navigation

Identifiers

PMID39090719
PMCPMC11295607

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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.