In brain tumor surgery, an appropriate and careful surgical planning process is crucial for surgeons and can determine the success or failure of the surgery. A deep comprehension of spatial relationships between tumor borders and surrounding healthy tissues enables accurate surgical planning that leads to the identification of the optimal and patient-specific surgical strategy. A physical replica of the region of interest is a valuable aid for preoperative planning and simulation, allowing the physician to directly handle the patient’s anatomy and easily study the volumes involved in the surgery. In the literature, different anatomical models, produced with 3D technologies, are reported and several methodologies were proposed. Many of them share the idea that the employment of 3D printing technologies to produce anatomical models can be introduced into standard clinical practice since 3D printing is now considered to be a mature technology. Therefore, the main aim of the paper is to take into account the literature best practices and to describe the current workflow and methodology used to standardize the pre-operative virtual and physical simulation in neurosurgery. The main aim is also to introduce these practices and standards to neurosurgeons and clinical engineers interested in learning and implementing cost-effective in-house preoperative surgical planning processes. To assess the validity of the proposed scheme, four clinical cases of preoperative planning of brain cancer surgery are reported and discussed. Our preliminary results showed that the proposed methodology can be applied effectively in the neurosurgical clinical practice both in terms of affordability and in terms of simulation realism and efficacy.

Current Practice in Preoperative Virtual and Physical Simulation in Neurosurgery / Elisa Mussi, Federico Mussa, Chiara Santarelli, Mirko Scagnet, Francesca Uccheddu, Rocco Furferi, Yary Volpe, Lorenzo Genitori. - In: BIOENGINEERING. - ISSN 2306-5354. - ELETTRONICO. - 7:(2020), pp. 1-14. [10.3390/bioengineering7010007]

Current Practice in Preoperative Virtual and Physical Simulation in Neurosurgery

Elisa Mussi;Chiara Santarelli;Francesca Uccheddu;Rocco Furferi;Yary Volpe;
2020

Abstract

In brain tumor surgery, an appropriate and careful surgical planning process is crucial for surgeons and can determine the success or failure of the surgery. A deep comprehension of spatial relationships between tumor borders and surrounding healthy tissues enables accurate surgical planning that leads to the identification of the optimal and patient-specific surgical strategy. A physical replica of the region of interest is a valuable aid for preoperative planning and simulation, allowing the physician to directly handle the patient’s anatomy and easily study the volumes involved in the surgery. In the literature, different anatomical models, produced with 3D technologies, are reported and several methodologies were proposed. Many of them share the idea that the employment of 3D printing technologies to produce anatomical models can be introduced into standard clinical practice since 3D printing is now considered to be a mature technology. Therefore, the main aim of the paper is to take into account the literature best practices and to describe the current workflow and methodology used to standardize the pre-operative virtual and physical simulation in neurosurgery. The main aim is also to introduce these practices and standards to neurosurgeons and clinical engineers interested in learning and implementing cost-effective in-house preoperative surgical planning processes. To assess the validity of the proposed scheme, four clinical cases of preoperative planning of brain cancer surgery are reported and discussed. Our preliminary results showed that the proposed methodology can be applied effectively in the neurosurgical clinical practice both in terms of affordability and in terms of simulation realism and efficacy.
2020
7
1
14
Goal 3: Good health and well-being for people
Elisa Mussi, Federico Mussa, Chiara Santarelli, Mirko Scagnet, Francesca Uccheddu, Rocco Furferi, Yary Volpe, Lorenzo Genitori
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1181250
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