The 3D Knee: Visualizing Real Data from 3D Magnetic Resonance Neurography
Johns Hopkins University
Established 2D MRI techniques are of limited clinical usefulness for visualizing of small peripheral cutaneous nerves of the knee due to limitations in spatial resolution and partial volume averaging effects. This leads clinicians to rely on their knowledge of anatomy, clinical evaluation, and diagnostic nerve blocks for diagnosis and treatment. Peripheral nerves have become increasingly visible with the development of new high-resolution 3T 3D MR techniques, with nerves peripheral nerves visible down to a diameter of less than 1 mm. (Fritz, personal interview, 2015) With increasing possibility for clinical integration comes greater need for teaching models correlated with Real Data, and increasing possibilities for accurate and efficient 3D visualization solutions for a variety of educational and clinical applications. Improvements in isotropic MR imaging data aquisition offer biomedical artists the opportunity to extrapolate 3D mesh from real patient data into 3D models of smaller and more complex anatomic features. 3D model creation also has the benefit of parenting many derivitive visualization solutions, including 3D derivative still images, 3D animations, and interactive 3D applications all from the same data, registered in 3D space, and useful in the creation of large multimedia projects for educational or clinical use. 3D surface mesh exports were taken from 3 Tesla high spatial resolution 3D MR data sets of the knee in OsiriX. Meshes were optimized in Meshlab, then a master 3D model of component parts created in ZBrush digital sculpting software. The model was textured and painted in Cinema 4D and Adobe Photoshop, and still images, 3D animated media, and 3D files were exported composed of the bones, ligaments, cartilage, muscles, vessels and most importantly nerves of the knee. These parallel 3D assets were used in the design and creation of an Interactive 3D application built in the Unity 3D game development engine. The real time 3D environment provides a platform for effective ontological learning. The application allows medical students, radiology residents, and radiology fellows to explore the 3D knee in an interactive manner, then switch seamlessly to linear defined learning applications created from still and animated content and radiological data, all correlated with the application’s master model. The workflow developed in this project for taking Real Data from MRI to interactive visualization can provide a useful path for the creation of future educational and clinical applications from radiological data. It is our hope that this project encourages future partnerships between biomedical illustrators and radiologists in developing better and more accurate visualization, which may education, and improve patient clinical outcome.
Interactive, 3D, Knee, peripheral nerve, MRN, Magnetic resonance neurography, MRI