• Amirhossein Mehbodniya, Mahmoud Moghavvemi, Vairavan Narayanan, Kalai A Muthusamy, Mohammad Hamdi, and Vicknes Waran.
• Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia.
• World Neurosurg. 2020 Feb 1; 134: e379-e386.

ObjectivesThe evaluation of sources of error when preparing, printing, and using 3-dimensional (3D) printed head models for training purposes.MethodsTwo 3D printed models were designed and fabricated using actual patient imaging data with reference marker points embedded artificially within these models that were then registered to a surgical navigation system using 3 different methods. The first method uses a conventional manual registration, using the actual patient's imaging data. The second method is done by directly scanning the created model using intraoperative computed tomography followed by registering the model to a new imaging dataset manually. The third is similar to the second method of scanning the model but eventually uses an automatic registration technique. The errors for each experiment were then calculated based on the distance of the surgical navigation probe from the respective positions of the embedded marker points.ResultsErrors were found in the preparation and printing techniques, largely depending on the orientation of the printed segment and postprocessing, but these were relatively small. Larger errors were noted based on a couple of variables: if the models were registered using the original patient imaging data as opposed to using the imaging data from directly scanning the model (1.28 mm vs. 1.082 mm), and the accuracy was best using the automated registration techniques (0.74 mm).ConclusionSpatial accuracy errors occur consistently in every 3D fabricated model. These errors are derived from the fabrication process, the image registration process, and the surgical process of registration.Copyright © 2019 Elsevier Inc. All rights reserved.

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