3D printing in neurosurgery

A new frontier in preoperative planning and surgical training

Cerebrovascular neurosurgery demands high-quality procedural outcomes in combination with optimal safety levels. Pathologies as aneurysms, AVM, and dural arteriovenous fistulae are often complex structures that require a deep understanding of their 3D configuration and of surrounding anatomical structures in order to treat them properly. However, the interpretation of medical images has historically been limited to two-dimensional (2D) media such as textbooks and computer screens. In contrast, 3D printers allow medical images to be converted into real 3D structures. ^, The main advantage of this technology is the noninvasive visualization of anatomical structures for diagnosis, surgical planning, and education for both trainees and patients. The possibility to create customized, high-resolution models is considered one of the most interesting innovations in surgical training, being at the same time a useful rehearsal for experienced surgeon facing very complex cases and a possibility of intensive and immersive training for residents. For these reasons, 3DP is considered an effective method of training, offering realistic anatomical reconstruction that may facilitate surgical skills acquisition, particularly in this era of reduced exposure to the operative room, as reported in a recent survey by the European Association of Neurosurgical Societies (EANS) Young Neurosurgeons and EANS Training Committee.

Surgical planning

Despite the evolution of radiologic imaging over past decades, with the introduction of 3D computed tomographic angiography (3D-CTA) and digital subtraction angiography (DSA) in daily practice, a great importance is given to the ability of the surgeon to mentally reconstruct very complex vascular anatomy and project it into patient's head. Even in the case of 3D rendering reconstruction, those images are often visualized on flat 2D screens, making the evaluation of depth and anatomical relationships between pathological and normal structures difficult. In this environment, the use of 3DP can provide real patient-specific and high-fidelity physical models ( Fig. 8.1 ), which can be visualized from any angle, representing a potentially more advantageous method of visualization. In addition, due to recent technical developments, this approach has become faster and cheaper, constituting a real amendment to traditional radiological techniques, enabling physical representation of complex vascular networks. In a recent systematic literature review by Randazzo et al. , 36 articles reported research experiences with 3DP in the neurosurgical field, 12 of which were related to cerebrovascular applications. This reflects a larger interest in this technique compared to other fields of neurosurgery like neurooncology, functional neurosurgery, or spine surgery, in which this technique is to date less represented in the literature. Surgical planning can be improved, thanks to 3D printed models also in some cases of pediatric patients needing treatment for AVMs and cranial malformations facilitating the approach and reducing the time of surgery. ^,

The use of artificial models for neurosurgical planning was described way before the 3DP technique was available. In 1986, Schultz et al. made use of 3D acrylic and plastic models to foreplan of a craniopagus twins' separation. Consultation with medical artists and prosthetists was important to create exact models of the patients. The use of physical models for planning surgery on craniopagus twins has been reported also in the “3D printing era”: A special emphasis is attributed to the importance of these models to understand 3D relationships between vascular structures that are shared by the twins. The possibility to simulate expendable models, bony and skin reconstruction as well the reproduction of venous anatomy that was correlated to cerebral angiography were proven particularly useful for surgical planning. The models were crucial to choose the most effective surgical strategy, after a 360 degrees anatomical evaluation, permitting the design of tailored instruments (surgical table, head holders, stereotactic frame …), allowing to better coordinate multiple teams. ^,

D'Urso et al. were the first to replicate the cerebral vasculature morphology of patients in a solid material. Nineteen artificial models were obtained by downloading native images from CTA and MRA onto a dedicated computer workstation. Raw image data were then converted to a format compatible with a stereolithography apparatus for manufacturing the models. Initial 3D reconstructions were performed using a volume rendering technique. The segmentation between vessels and bone was achieved by image thresholding and structures unconnected to the main arterial tree were removed using a 3D connectivity function. The contour data were then used to create the final object file that was sent to the stereolithography device. In the manufacturing process, a laser beam solidified layers of a photosensitive liquid resin monomer according to the cerebral vasculature contours. The resulting object was then rigidified in an ultraviolet oven. The utility of these models was subjectively assessed by the neurosurgeons in charge after the operation. They reported that the 3D models accurately represented the cerebral vasculature and the aneurysm relationships except in one case (in a patient who presented an endosaccular thrombus). Thus, this tactile anatomic overview would help even an inexperienced surgeon to quickly understand the spatial organization of the aneurysm without requiring a complex mental reconstruction from multiple images or replacement of the vascular volume. The authors reported that the models helped to position the patient's head with respect to the most appropriate approach angle and were also helpful for understanding the 3D anatomy, giving the surgeon more confidence during the procedure. It was also possible to try the appropriate aneurysm clip in terms of length, shape, and orientation on the artificial model ( Fig. 8.2 ), thereby developing a new type of direct simulation. ^,

Kimura et al. made 3D elastic hollow models of individual cerebral aneurysms for the purpose of preoperative simulation and surgical training (3 retrospective and 7 prospective cases). They also applied a stereolithographic technique and used a prototyping machine to build the model from a rubber-like polymer hardened under ultraviolet light, according to the vessel wall anatomy. The aneurysm model was then fixed with either flexible wires or plastic clay, according to the selected approach, and oriented along the surgical view. Finally, under the operating microscope, various types of aneurysm clips were applied to determine the most appropriate size, shape, and orientation. In one case of a deep-seated vertebrobasilar aneurysm, they designed a solid 3D model that included the aneurysm, vessels, and cranial base bone. They then created a craniotomy and simulated the access to the aneurysm. The goal of developing these models was to represent a real 3D arterial tree in order to simulate preoperatively the surgical repair of intracranial aneurysms (with regard to selection of clip properties and orientation). This technique might also assist young neurosurgeons in developing their own surgical strategy and allow them to confront the potential difficulties of an approach and clip application in a narrow corridor. Unfortunately, these simulation techniques lack any representation of surrounding brain structures, which is one of the main aspects restricting accessibility and maneuverability during aneurysm surgery. Furthermore, when looking at anatomic accuracy, the authors acknowledged difficulties in replicating small arteries and avoiding contamination of the solid 3D models by venous components that could only be distinguished from the arterial component by an experienced vascular neurosurgeon. In two cases using these models, the aneurysm neck was also poorly depicted because of the limited definition of native images combined with suboptimal segmentation of the vasculature, which is operator dependent. Another drawback of these methods is the absence of information concerning the thickness or biomechanical properties of the aneurysm wall and parent vessels, which could be useful in predicting their deformability during clipping. Although these interesting techniques are quite expensive and the preparation of a single model takes usually several days, making such simulations is not applicable to emergency situations like ruptured intracranial aneurysms. ^,

Kondo et al. reported their experience with 22 patients where unruptured intracranial aneurysms were reproduced in 3D printed models from 3D-CTA. The authors found that the microsurgical anatomy of skull bones, main arteries, and the vascular lengths was molded with high-level accuracy, concluding that 3D printed models prepared by this procedure are useful for neurosurgical simulation.

Endovascular applications

Numerous groups have reported encouraging results in terms of accuracy in reproducing complex vascular structures using this technology. ^{, , ,} Based on existing publications, significant differences between preoperative imaging and 3D printed models were only observed in a few cases and on specific areas, attesting to the accuracy and fidelity in reproducing intracranial vessels and surrounding anatomical structures. In particular, Ionita et al. used a printer able to manufacture 3D phantoms with up to 17 different materials to reproduce endovascular models for clot-retrieving procedures in case of an ischemic stroke. They were able to print ultrafine 16 μm layers, which is ideal for details, complex geometries, and very thin walls (as it is for intracranial vascular structures). For rigid materials, the accuracy in each printed plane was between 20 and 85 μm for features smaller than 50 mm and up to 200 μm for full model size. The net printing area was 255 × 252 × 200 mm. For soft materials, the layer-resolution was about 32 μm and up to 200 μm in-plane accuracy. The phantoms were tested in three steps: X-ray imaging, procedure simulations, and cone beam computerized tomography (CT) for geometry accuracy verification. Each phantom was connected to a peristaltic pump, and planar and rotational angiography was performed on each one. For complex phantoms, vessel patency and qualitative assessment of the flow were obtained. The phantom models are extremely accurate; the geometry differences between the phantom and the patient geometry were of the order of the voxel size, less than 125 μm. This benefit makes this technology very useful for device development testing and medical research. Mechanical behavior of the catheter and the haptic feedback sensed by the interventionist were very similar to that experienced clinically. Clots were easy to deliver at the desired location, and they were not removed by the flow in the system. Sometimes clot fragmentation occurred because of the procedure and resulted in blockage of more distal branches, similarly to situations seen in some clinical cases. To demonstrate the accuracy and the reliability of the 3D printed models, Namba et al. tried to determine the shape of the microcatheter inserted for aneurysm coiling and were able to correctly predict it in 10 consecutive patients.

Surgical training

Printed vascular networks have been utilized to replicate hemodynamics within an aneurysm and to practice clipping procedures: through a better understanding of vascular anatomy, this technology seems to lead to an easier surgical planning. ^, To assess the potential application in neurovascular training, Mashiko et al. used three patient-specific models composed of a trimmed skull, an elastic, retractable brain, and a hollow elastic aneurysm with its parent artery. The brain models were created using 3D printers via a casting technique, whereas the artery models were made by 3DP and a lost-wax technique. Trainees succeeded in performing the simulation in line with an actual surgery, and their skills tended to improve upon completion of the training. Based on existing experiences, we can imagine that in the future, the use of 3D printed phantoms will play a more important role in surgical training, partially replacing the standard training on cadavers ( Fig. 8.3 ). The principal advantage of 3DP is that it is possible to reproduce a real disease, in order to reproduce and subsequently train on real cases, making it possible to reproduce it every time needed.