Evidence map›Paper›PMID 38752081›Full record

ArticleCureus2024

An Image-Based Augmented Reality System for Achieving Accurate Bone Resection in Total Knee Arthroplasty.

Hyoung-Taek Hong, Yong-Gon Koh, Byung Woo Cho, Hyuck Min Kwon, Kwan Kyu Park, Kyoung-Tak Kang

Abstract read
In one paragraph

Article in Cureus, 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.

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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

6 authors.

Hyoung-Taek HongSkyve R&D LAB, Skyve Co. LTD., Seoul, KOR.
Yong-Gon KohJoint Reconstruction Center, Department of Orthopedic Surgery, Yonsei Sarang Hospital, Seoul, KOR.
Byung Woo ChoDepartment of Orthopedic Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, KOR.
Hyuck Min KwonDepartment of Orthopedic Surgery, Yonsei University College of Medicine, Seoul, KOR.
Kwan Kyu ParkDepartment of Orthopedic Surgery, Yonsei University College of Medicine, Seoul, KOR.
Kyoung-Tak KangSkyve R&D LAB, Skyve Co. LTD., Seoul, KOR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objective With the steady advancement of computer-assisted surgical techniques, the importance of assessing and researching technology related to total knee arthroplasty (TKA) procedures has increased. Augmented reality (AR), a recently proposed next-generation technology, is expected to enhance the precision of orthopedic surgery by providing a more efficient and cost-effective approach. However, the accuracy of image-based AR in TKA surgery has not been established. Therefore, this study aimed to determine whether accurate bone resection can be achieved in TKA surgery using image-based AR. Methods In this study, we replaced traditional CT imaging and reconstructions for creating a bone 3D model by direct 3D scanning of the femur and tibia. The preoperative planning involved identifying anatomical landmarks and determining the surgical details. During surgery, markers were employed to create a local coordinate system for an AR-assisted surgical system using a Polaris camera. This approach helped minimize discrepancies between the 3D model and actual positioning, ensuring accurate alignment. Results The AR-assisted surgery using the image method resulted in fewer errors [average error: 0.32 mm; standard deviation (SD): 0.143] between the bone resection depth of the preoperative surgical plan and the bone model test results. Conclusions Our findings demonstrated the accuracy of bone resectioning by using image-based AR-assisted navigation for TKA surgery. Image-based AR-assisted navigation in TKA surgery is a valuable tool not only for enhancing accuracy by using smart glasses and sensors but also for improving the efficiency of the procedure. Therefore, we anticipate that image-based AR-assisted navigation in TKA surgery will gain wide acceptance in practice.

Indexed as

augmented realitycomputer assisted surgeryhealthcare tech contestimage basednavigationtotal knee arthroplasty

Identifiers

PMID38752081
PMCPMC11094513

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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.