Download PDF
J Neurol Surg A Cent Eur Neurosurg
DOI: 10.1055/a-2726-3537
Original Article

Patient-Specific Computed Tomography-Based Three-Dimensional Spine Trauma Models for Preoperative Planning in Virtual Reality and 3D Printing: An EANS Young Neurosurgeons' Network Study

Authors

  • Martin Trandzhiev

    1   Department of Neurosurgery, Acibadem City Clinic University Hospital Tokuda, Sofia, Bulgaria

  • Erik Schulz

    2   Department of Neurosurgery, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland
    3   Spine Center of Eastern Switzerland, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland

  • Martin N. Stienen

    2   Department of Neurosurgery, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland
    3   Spine Center of Eastern Switzerland, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland

  • Oliver Bozinov

    2   Department of Neurosurgery, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland
    3   Spine Center of Eastern Switzerland, Kantonsspital St. Gallen and Medical School of St. Gallen, St. Gallen, Switzerland

  • Cateno Petralia

    4   Department of Neurosurgery, Policlinico “G.Rodolico – San Marco,” University Hospital Catania, Catania, Italy

  • Carmelo Vitaliti

    4   Department of Neurosurgery, Policlinico “G.Rodolico – San Marco,” University Hospital Catania, Catania, Italy

  • Martina Rossitto

    4   Department of Neurosurgery, Policlinico “G.Rodolico – San Marco,” University Hospital Catania, Catania, Italy

  • Daniel Alvarado Flores

    4   Department of Neurosurgery, Policlinico “G.Rodolico – San Marco,” University Hospital Catania, Catania, Italy

  • Giuseppe M.V. Barbagallo

    4   Department of Neurosurgery, Policlinico “G.Rodolico – San Marco,” University Hospital Catania, Catania, Italy

  • Vincenzo Fanelli

    5   Department of Neurosurgery, Miulli General Regional Hospital, Acquaviva delle Fonti-Bari, Bari, Italy

  • Mary Solou

    6   Department of Neurosurgery, General University Hospital Attikon, Attikon University Hospital, Athens, Greece

  • Efstathios J. Boviatsis

    6   Department of Neurosurgery, General University Hospital Attikon, Attikon University Hospital, Athens, Greece

  • Dimitrios Dimopoulos

    7   Department of Neurosurgery, Evangelismos Athens General Hospital, Athens, Attica, Greece

  • Vivek Sanker

    8   Department of Neurosurgery, Stanford University, California, United States

  • Antonia Vogt

    9   Division of Trauma and Orthopaedic Surgery, Addenbrooke's Hospital, Cambridge, England, United Kingdom of Great Britain and Northern Ireland

  • Vladimir Nakov

    1   Department of Neurosurgery, Acibadem City Clinic University Hospital Tokuda, Sofia, Bulgaria

  • Diogo Belo

    10   Department of Neurosurgery, Centro Hospitalar Lisboa Norte, Lisbon, Portugal

  • Evangelos Drosos

    11   University Hospitals Bristol and Weston, NHS Foundation Trust, Bristol, United Kingdom

  • Maria L. Gandía-González

    12   Department of Neurosurgery, Hospital Universitario La Paz, Madrid, Spain

  • Toma Spiriev

    1   Department of Neurosurgery, Acibadem City Clinic University Hospital Tokuda, Sofia, Bulgaria

  • Giovanni Raffa

    13   Division of Neurosurgery, BIOMORF Department, University of Messina, Italy

Funding Information None.
Further Information
Also available at
   Permissions and Reprints

Abstract

Background and Study Objective

Lately, the wide availability of open-source modelling and rendering software in neurosurgery has led to the development of a methodological pipeline for creating patient-specific three-dimensional (3D) models based on preoperative imaging data. With recent innovations in virtual reality (VR) technology and 3D printing, these models can be applied to enhance preoperative planning and medical training. The main question this paper aims to answer is whether the proposed algorithm of intensity-based CT segmentation and basic 3D modelling is adequate to create a reference library of patient-specific models, categorized according to the AO Spine Injury Classification System, and suitable for VR and 3D printing-based preoperative planning.

Materials and Methods

We used the open-source medical image viewer Horos to create volumetric renderings of CT scans of trauma patients from several European centers. The models were postprocessed using 3D modelling software and exported in appropriate formats for VR or 3D printing.

Results

We created 37 models of trauma patients, spanning from the upper cervical to the thoracolumbar segment, categorized according to the AO Spine Injury Classification System. Additionally, a remote case discussion conducted by uploading these models into a collaborative VR environment was demonstrated as a proof of concept.

Conclusion

In the present study, we demonstrated that open-source software can create a database of patient-specific 3D models. Additionally, the communication between remote departments can be facilitated by uploading these models into a collaborative VR environment, and the comprehensive evaluation of spine fractures fostered through 3D printing. Further studies are needed to assess the database's educational value.

Keywords

3D spine models - spine trauma - virtual reality - AO spine - classification - education


Publication History

Received: 23 May 2025

Accepted: 17 October 2025

Article published online:
29 December 2025

© 2025. Thieme. All rights reserved.

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany