J Neurol Surg B Skull Base 2019; 80(S 01): S1-S244
DOI: 10.1055/s-0039-1679701
Poster Presentations
Georg Thieme Verlag KG Stuttgart · New York

Patient-Specific Three-Dimensionally Printed Models for Presurgical Planning, Training, and Patient Education in Skull Base Surgery

Sandip S. Panesar
1   Department of Neurosurgery, Stanford University, Stanford, California, United States
,
Kumar Abhinav
1   Department of Neurosurgery, Stanford University, Stanford, California, United States
,
Michael Magnetta
2   Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
,
Debraj Raj Mukherjee
3   Department of Neurosurgery, Johns Hopkins, Baltimore, Maryland, United States
,
Paul Gardner
4   Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
,
Juan C. Fernandez-Miranda
1   Department of Neurosurgery, Stanford University, Stanford, California, United States
› Author Affiliations
Further Information

Publication History

Publication Date:
06 February 2019 (online)

 

Background and Objectives: The complex anatomy of the skull base represents a significant learning curve and planning challenge for surgeons. Routine preoperative imaging sequences often do not provide adequate information about involved cranial nerve structures due to their small size or distortion by tumors. Uses of 3D printing in neurosurgery are being explored. One potential use of 3D printing is to create patient-specific 3D models demonstrating relevant anatomy including pathology and surrounding structures including vessels and nerves. These models may act as an adjunct to presurgical neuroimaging and provide a tactile, manipulatable reference for the surgeon prior to, and during surgery. We aimed to create 3D printed models of various skull base pathologies to qualitatively study their surgical applications.

Methods: Two cases of petroclival meningioma (PCM) and a case of trigeminal neuralgia (TGN) secondary to vascular impingement were selected. For the PCM cases, preoperative computerized tomography (CT) angiography sequences were used to model bony, vascular and tumor structures. For the TGN case, a magnetic resonance imaging (MRI) fast imaging employing steady-state acquisition (FIESTA) sequence was used. Mimics Medical v20.0 (Materialise Inc., Belgium) was used to create virtual models (in 3D-printable .stl format) using DICOM CT and MRI sequences. The models were printed using Form 2 (Formlabs, Cambridge) 3D printers. We used two types of acrylic resin (Formlabs) to print the models. For the PCM cases, osseus, tumor and vasculature were printed separately. For the TGN case, a single model was printed. Volume of resin, printing time and cost varied per model ([Table 1]). Once printed and washed in isopropyl alcohol, the models were hand-painted to highlight arterial, venous and neural structures.

Table 1

Table showing the time taken to model and print 3 cases (PCM 1/2: petroclival meningioma cases 1 and 2; TGN: trigeminal neuralgia case)

PCM 1

PCM 2

TGN

Modelling time (h)

8

4

8

Resin volume (cc)

220.23

422.56

48.33

Estimated cost (U.S. $)

33.00

63.40

9.70

Results: The first PCM model assumed a left sagittal hemisection of the skull, with the meningioma and relevant arterial structures. The second PCM model removed a coronal slice of the posterior skull, demonstrating the centrally located meningioma and the bilateral vasculature. Tumors and vasculature could be collectively removed for detailed study. The brainstem, cranial nerves, arteries and veins were all represented by a single model for the TGN case. It clearly depicted vascular impingement of CN V by the superior cerebellar artery.

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Fig. 1
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Conclusion: We have demonstrated that 3D printing of patient-specific models is a viable and affordable option. These models can be used to enhance resident training and for patient education. Modelling, printing and painting delicate cranial nerve structures is a challenge due to their size. Use of 3D printers capable of printing directly in different colored resin may address this issue.