Mobile, real-time, and point-of-care augmented reality is robust, accurate, and feasible: a prospective pilot study

  • Hannes Götz Kenngott
  • Anas Amin Preukschas
  • Martin Wagner
  • Felix Nickel
  • Michael Müller
  • Nadine Bellemann
  • Christian Stock
  • Markus Fangerau
  • Boris Radeleff
  • Hans-Ulrich Kauczor
  • Hans-Peter Meinzer
  • Lena Maier-Hein
  • Beat Peter Müller-Stich
Dynamic Manuscript
  • 74 Downloads

Abstract

Background

Augmented reality (AR) systems are currently being explored by a broad spectrum of industries, mainly for improving point-of-care access to data and images. Especially in surgery and especially for timely decisions in emergency cases, a fast and comprehensive access to images at the patient bedside is mandatory. Currently, imaging data are accessed at a distance from the patient both in time and space, i.e., at a specific workstation. Mobile technology and 3-dimensional (3D) visualization of radiological imaging data promise to overcome these restrictions by making bedside AR feasible.

Methods

In this project, AR was realized in a surgical setting by fusing a 3D-representation of structures of interest with live camera images on a tablet computer using marker-based registration. The intent of this study was to focus on a thorough evaluation of AR. Feasibility, robustness, and accuracy were thus evaluated consecutively in a phantom model and a porcine model. Additionally feasibility was evaluated in one male volunteer.

Results

In the phantom model (n = 10), AR visualization was feasible in 84% of the visualization space with high accuracy (mean reprojection error ± standard deviation (SD): 2.8 ± 2.7 mm; 95th percentile = 6.7 mm). In a porcine model (n = 5), AR visualization was feasible in 79% with high accuracy (mean reprojection error ± SD: 3.5 ± 3.0 mm; 95th percentile = 9.5 mm). Furthermore, AR was successfully used and proved feasible within a male volunteer.

Conclusions

Mobile, real-time, and point-of-care AR for clinical purposes proved feasible, robust, and accurate in the phantom, animal, and single-trial human model shown in this study. Consequently, AR following similar implementation proved robust and accurate enough to be evaluated in clinical trials assessing accuracy, robustness in clinical reality, as well as integration into the clinical workflow. If these further studies prove successful, AR might revolutionize data access at patient bedside.

Keywords

Augmented reality Mobile device Image visualization Visual assistance 

Notes

Acknowledgements

The current study was conducted within the setting of the Research Training Group 1126 (“Development of New Computer-Based Methods for the Future Workplace in Surgery”) and the Collaborative Research Center 125 (“Cognition Guided Surgery”); both were funded by the German Research Foundation.

Compliance with ethical standards

Disclosures

Drs. Hannes Götz Kenngott, Anas Amin Preukschas, Martin Wagner, Felix Nickel, Michael Müller, Nadine Bellemann, Christian Stock, Markus Fangerau, Boris Radeleff, Hans-Ulrich Kauczor, Hans-Peter Meinzer, Lena Maier-Hein, and Beat Peter Müller-Stich have no conflicts of interest or financial ties to disclose.

Supplementary material

Supplementary material 1 (MP4 29711 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Hannes Götz Kenngott
    • 1
  • Anas Amin Preukschas
    • 1
  • Martin Wagner
    • 1
  • Felix Nickel
    • 1
  • Michael Müller
    • 4
  • Nadine Bellemann
    • 2
  • Christian Stock
    • 3
  • Markus Fangerau
    • 2
  • Boris Radeleff
    • 2
  • Hans-Ulrich Kauczor
    • 2
  • Hans-Peter Meinzer
    • 4
  • Lena Maier-Hein
    • 4
  • Beat Peter Müller-Stich
    • 1
  1. 1.Department of General, Visceral and Transplantation SurgeryHeidelberg UniversityHeidelbergGermany
  2. 2.Department of Diagnostic and Interventional RadiologyHeidelberg UniversityHeidelbergGermany
  3. 3.Institute for Medical Biometry and InformaticsHeidelberg UniversityHeidelbergGermany
  4. 4.Division of Medical and Biological InformaticsGerman Cancer Research CenterHeidelbergGermany

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