A mixed-reality approach to radiation-free training of C-arm based surgery

Philipp Stefan, Séverine Habert, Alexander Winkler, Marc Lazarovici, Julian Fürmetz, Ulrich Eck, Nassir Navab

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The discrepancy of continuously decreasing clinical training opportunities and increasing complexity of interventions in surgery has led to the development of different training options like anatomical models, computer-based simulators or cadaver trainings. However, trainees, following this training and ultimately performing patient treatment, still face a steep learning curve. To address this problem for C-arm based surgery, we introduce a realistic radiation-free simulation system that combines patient-based 3D printed anatomy and simulated X-ray imaging using a physical C-arm. This mixed reality simulation system facilitates a transition to C-arm based surgery and has the potential to complement or even replace large parts of cadaver training and to reduce the risk for errors when proceeding to patient treatment. In a technical evaluation, we show that our system simulates X-ray images accurately with an RMSE of 1.85 mm compared to real X-ray imaging. To explore the fidelity and usefulness of the proposed mixed reality system for training and assessment, we conducted a user study. Six surgical experts performed a facet joint injection on the simulator and rated aspects of the system on a 5-point Likert scale. They expressed agreement with the overall realism of the simulation and strong agreement with the usefulness of such a mixed reality system for training of novices and experts.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
EditorsPierre Jannin, Simon Duchesne, Maxime Descoteaux, Alfred Franz, D. Louis Collins, Lena Maier-Hein
PublisherSpringer Verlag
Pages540-547
Number of pages8
ISBN (Print)9783319661841
DOIs
StatePublished - 2017
Event20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 11 Sep 201713 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10434 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period11/09/1713/09/17

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