# Production of Synthetic Models for Neuro-Oncology Training by Additive Manufacturing
## 1 Introduction  
Additive manufacturing (AM), commonly known as 3D printing, is one of the greatest manufacturing revolutions. It consists in the creation of physical objects by successively joining material, layer upon layer, according to the corresponding 3D model data. AM technologies have opened new paths for the manufacture of products, with application in several fields [1]. In the medical sector, AM has had a great relevance due to the customization and freeform capabilities, which allows for the production of personalized implants and tools, as well as the production of real-case anatomic models [2]. In the field of neurosurgery, AM has had a great impact as it enables the production of anatomically specific models of patients with diseases, allowing for the acquisition of surgical skills with the testing of these simulated models before facing real surgery, planning a future intervention by having the possibility of previewing the physical organ in all its perspectives. This makes these 3D models an excellent tool for teaching and surgical training without risk of harm to the patient [3]. In producing a 3D printed anatomical model, the first step consists in obtaining the images provided by a scanning technique such as computed tomography (CT). These images, usually in a DICOM (Digital Imaging and Communication on Medicine) format, are then processed in a specific software (e.g., 3 DSlicer) to obtain the segmented model of the tissue of interest. This model is transformed into a STL file that can be imported in a design program or, in some cases, directly 3D printed. This approach for obtaining anatomical models for teaching and surgical training has been used by several authors. [PERSON] et al. reviewed numerous works about the employment of 3D printing to create three-dimensional models for surgical training in the case of different pathologies [4]. Among them, [PERSON] et al. (2015) produced the 3D printing of models for clipping of cerebral aneurysms [5]. They manufactured an aneurysm model that simulated the geometry and texture of the real organ. Other examples of brain aneurysm fabrication were provided by [PERSON] et al. [6] and [PERSON] et al. [7]. On the other hand, [PERSON] et al. also described the contribution of several authors regarding models of skulls and tumors. [PERSON] et al. [8] used AM to create an anatomical model with brain pathologies to enhance the neurosurgeons educational experience, which included simulated models in texture and geometry of the skull, brain, tumor, and dura mater. [PERSON] et al. [9] and [PERSON] et al. [10] manufactured all the previous models and included a brain aneurysm in order to perform the surgical clipping intervention with these simulated models. [PERSON] et al. [11] and [PERSON] et al. [12] conducted research on the 3D printing of skulls and tumors using different techniques, allowing, among others, to print models with multiple materials and colors. Finally, [PERSON] et al. also produced models of specific brain tumors to use in daily clinical practice for neurosurgery [13]. Training in neurosurgery is a long-term process, which lasts in European countries for at least 6-7 years, necessary for learning the basic maneuvers, followed by continuous training throughout one's career. This long training process involves high costs for the health system and a higher risk in the medical act, taking into account that every new technical procedure that a surgeon performs will be done on a real patient. For these reasons, the employment of synthetic models by AM is considered a promising approach for the neurosurgeons training, but, according to the literature [14; 15], most of the training models developed thus far for neurosurgery do not combine the realism of the model with economic manufacturing procedures. This is of special relevance for training applications where several replicas of the same real case are needed.