The original grayscale images were used to manually segment the cranial nerves. The images were manually segmented using Photoshop, implementing the magic wand tool in high-magnification views - a time-consuming project. JPEG images were the foundation for 3D reconstruction of a rough model of cranial nerves I-XII as they exit the brain stem. The model began with a set of high-resolution MR images of the brain exported with window and level settings that enabled the cranial nerves to be well-visualized in the background of cerebrospinal fluid. Software included 3D Studio Max (Autodesk), Photoshop (Adobe), OsiriX Lite, a Mac-based PACS, and Mimics (Materialise) to create the stereolithography (STL) files, which could alternatively be created without proprietary software but with additional processing time. The design work was performed on an Apple MacBook. The components should ideally be from the same patient however, design software can adjust the pieces from multiple patients after reconstruction, if needed. Fitting the components together is an important design element, so that the pieces are easily put together and easily separable. The three components of the model included the cranial nerves the brain stem, which served as the trunk of the cranial nerves and the osseous skull base. This project sought to build a more functional and workable cranial nerve and brain stem model than was available previously. A detailed model could be used to practice surgical procedures such as neurovascular decompression microsurgery for trigeminal neuralgia, or resection of vestibular schwannoma and cerebellopontine angle masses, the team wrote. The only commercially available physical models tend to be of the entire brain and contain only the root entry zone, lacking the entire course of cranial nerves fitting into the skull base and also customizability.īetter cranial nerve models are needed not only for surgical planning, but also for surgical simulation. There are few publications covering custom 3D printing of cranial nerve models, the authors wrote. Knowing the expected course of the nerves is important for subspecialty-level neuroimaging interpretation. "What this adds to pure cross-sectional imaging is a significantly improved three-dimensional understanding of the anatomy, which at times is not well-visualized on imaging due to their small size, imaging technique, presence of artifacts, or distortion by pathologic processes such as tumors," Javan said. The resulting models can be used for teaching purposes for neuroradiology fellows and residents rotating through their section, Javan wrote in an email. The result was a durable and accurate 3D-printed model of the cranial nerves using actual patient MR and CT images of the cerebellopontine angle and skull base, according to Dr. Ramin Javan and colleagues ( JDI, February 21, 2017). Image of 3D-printed cranial nerve model created from MR and CT images of the cerebellopontine angle and skull base.
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