3D-modeling of sternal chondrosarcomas from angio-CT-Scan: Clinical application and surgical perspectives

Malignant bone tumors of the sternum are rare. Their surgical treatment remains largely based on precise knowledge of preoperative imaging in order to define appropriate margins during tumor resection. We provide a practical 3-dimensional (3D) modeling method to better understand the relationships b...

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Veröffentlicht in:Annals of 3D printed medicine 2021-03, Vol.1, p.100003, Article 100003
Hauptverfasser: Burgade, R., Uhl, J.F., Prat, G.D., Ruiz, C., Lorea, B., Delmas, V., Rosset, P., Le-Nail, L.R.
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Sprache:eng
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Zusammenfassung:Malignant bone tumors of the sternum are rare. Their surgical treatment remains largely based on precise knowledge of preoperative imaging in order to define appropriate margins during tumor resection. We provide a practical 3-dimensional (3D) modeling method to better understand the relationships between these tumors and neighboring organs. Axial view images from CT-scans were processed by the open source software Horos® after anonymization. A first surface reconstruction was carried out by the software to form a digital mesh. This raw model was processed by Meshmixer® software (Autodesk™) in order to remove artefacts. These models underwent a surface reduction of the mesh using Meshlab® software and were hosted on a secure private platform. Six angio CT-Scan were performed in three patients with chondrosarcomas of the sternum. The segmentation of organs and vessels has made it possible to create a real 3-D anatomical board. Each of these protected models can be viewed on our server and can be manipulated virtually on 360° using the secure links provided in this article. 3D vision was available using inexpensive cardboard virtual reality glasses. The use of computer modeling could help in the teaching of anatomy, but also in the understanding of the disease by the patient himself. One of the perspectives would be the 3D printing of biocompatible materials in order to carry out tailor-made reconstructions.
ISSN:2666-9641
2666-9641
DOI:10.1016/j.stlm.2020.100003