Evidence map›Paper›PMID 33166252›Full record

ArticleIEEE transactions on medical imaging2021

Development and Pre-Clinical Analysis of Spatiotemporal-Aware Augmented Reality in Orthopedic Interventions.

Javad Fotouhi, Arian Mehrfard, Tianyu Song, Alex Johnson, Greg Osgood, Mathias Unberath, Mehran Armand, Nassir Navab

Abstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Cannula-mounted Robots for Semi-autonomous Vertebroplasty: A Comparison of Piezo-based and Screw-based Inchworm Drive Designs.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2025
    Article
  3. STTAR: Surgical Tool Tracking Using Off-the-Shelf Augmented Reality Head-Mounted Displays.IEEE transactions on visualization and computer graphics · 2024
    Article
  4. Mixed Reality Interfaces for Achieving Desired Views with Robotic X-ray Systems.Computer methods in biomechanics and biomedical engineering. Imaging & visualization · 2023
    Article
  5. Article
  6. Article
  7. 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.

Javad Fotouhi
Arian Mehrfard
Tianyu Song
Alex Johnson
Greg Osgood
Mathias Unberath
Mehran Armand
Nassir Navab

Funding

Image-Guided Workstation and Tools for the Treatment of Bone DefectsR01EB016703 · NIBIB · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI ARMAND, MEHRAN · 2013 to 2022
$3.4M
Robotic System for Spinal Decompression and Interbody FusionR01AR080315 · NIAMS · UNIVERSITY OF ARKANSAS AT FAYETTEVILLE · PI ARMAND, MEHRAN, JAIN, AMIT · 2022 to 2025
$1.7M
Robot-Assisted Femoroplasty with Intraoperative Biomechanical FeedbackR01EB023939 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ARMAND, MEHRAN · 2017 to 2020
$1.6M
NIAMS NIH HHS R01 AR080315NIBIB NIH HHS R01 EB016703NIBIB NIH HHS R01 EB023939
6 · The paper itself

Abstract

Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. As a consequence, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions. The main contribution of this paper is to reveal how exemplary workflows are redefined by taking full advantage of head-mounted displays when entirely co-registered with the imaging system at all times. The awareness of the system from the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. Our system achieved an error of 4.76 ± 2.91mm for placing K-wire in a fracture management procedure, and yielded errors of 1.57 ± 1.16° and 1.46 ± 1.00° in the abduction and anteversion angles, respectively, for total hip arthroplasty (THA). We compared the results with the outcomes from baseline standard operative and non-immersive AR procedures, which had yielded errors of [4.61mm, 4.76°, 4.77°] and [5.13mm, 1.78°, 1.43°], respectively, for wire placement, and abduction and anteversion during THA. We hope that our holistic approach towards improving the interface of surgery not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications and provide novel approaches of documenting procedures for training purposes.

Indexed as

Augmented RealitySurgery, Computer-AssistedHumans

Identifiers

PMID33166252
PMCPMC8317976

What OpenQuestion holds

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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.