3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms

We developed a practical and cost-effective method of production of a 3D-printed model of the arterial Circle of Willis of patients treated because of an intracranial aneurysm. We present and explain the steps necessary to produce a 3D model from medical image data, and express the significant value...

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Autores principales: Błaszczyk, Maciej, Jabbar, Redwan, Szmyd, Bartosz, Radek, Maciej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000886/
https://www.ncbi.nlm.nih.gov/pubmed/33805774
http://dx.doi.org/10.3390/jcm10061201
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author Błaszczyk, Maciej
Jabbar, Redwan
Szmyd, Bartosz
Radek, Maciej
author_facet Błaszczyk, Maciej
Jabbar, Redwan
Szmyd, Bartosz
Radek, Maciej
author_sort Błaszczyk, Maciej
collection PubMed
description We developed a practical and cost-effective method of production of a 3D-printed model of the arterial Circle of Willis of patients treated because of an intracranial aneurysm. We present and explain the steps necessary to produce a 3D model from medical image data, and express the significant value such models have in patient-specific pre-operative planning as well as education. A Digital Imaging and Communications in Medicine (DICOM) viewer is used to create 3D visualization from a patient’s Computed Tomography Angiography (CTA) images. After generating the reconstruction, we manually remove the anatomical components that we wish to exclude from the print by utilizing tools provided with the imaging software. We then export this 3D reconstructions file into a Standard Triangulation Language (STL) file which is then run through a “Slicer” software to generate a G-code file for the printer. After the print is complete, the supports created during the printing process are removed manually. The 3D-printed models we created were of good accuracy and scale. The median production time used for the models described in this manuscript was 4.4 h (range: 3.9–4.5 h). Models were evaluated by neurosurgical teams at local hospital for quality and practicality for use in urgent and non-urgent care. We hope we have provided readers adequate insight into the equipment and software they would require to quickly produce their own accurate and cost-effective 3D models from CT angiography images. It has become quite clear to us that the cost-benefit ratio in the production of such a simplified model is worthwhile.
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spelling pubmed-80008862021-03-28 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms Błaszczyk, Maciej Jabbar, Redwan Szmyd, Bartosz Radek, Maciej J Clin Med Article We developed a practical and cost-effective method of production of a 3D-printed model of the arterial Circle of Willis of patients treated because of an intracranial aneurysm. We present and explain the steps necessary to produce a 3D model from medical image data, and express the significant value such models have in patient-specific pre-operative planning as well as education. A Digital Imaging and Communications in Medicine (DICOM) viewer is used to create 3D visualization from a patient’s Computed Tomography Angiography (CTA) images. After generating the reconstruction, we manually remove the anatomical components that we wish to exclude from the print by utilizing tools provided with the imaging software. We then export this 3D reconstructions file into a Standard Triangulation Language (STL) file which is then run through a “Slicer” software to generate a G-code file for the printer. After the print is complete, the supports created during the printing process are removed manually. The 3D-printed models we created were of good accuracy and scale. The median production time used for the models described in this manuscript was 4.4 h (range: 3.9–4.5 h). Models were evaluated by neurosurgical teams at local hospital for quality and practicality for use in urgent and non-urgent care. We hope we have provided readers adequate insight into the equipment and software they would require to quickly produce their own accurate and cost-effective 3D models from CT angiography images. It has become quite clear to us that the cost-benefit ratio in the production of such a simplified model is worthwhile. MDPI 2021-03-13 /pmc/articles/PMC8000886/ /pubmed/33805774 http://dx.doi.org/10.3390/jcm10061201 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Błaszczyk, Maciej
Jabbar, Redwan
Szmyd, Bartosz
Radek, Maciej
3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title_full 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title_fullStr 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title_full_unstemmed 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title_short 3D Printing of Rapid, Low-Cost and Patient-Specific Models of Brain Vasculature for Use in Preoperative Planning in Clipping of Intracranial Aneurysms
title_sort 3d printing of rapid, low-cost and patient-specific models of brain vasculature for use in preoperative planning in clipping of intracranial aneurysms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000886/
https://www.ncbi.nlm.nih.gov/pubmed/33805774
http://dx.doi.org/10.3390/jcm10061201
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