Error Minimization in Pre-surgical Model of Brain Tumor for 3-D Printing

Brain cancer treatment options vary in many ways and include surgical procedures, radiotherapy, and chemotherapy. The neurosurgeons typically uses 2-D MRI images for preoperative planning and execution of surgery. The determination of the size of the tumor and its exact location is of utmost necessity for planning the safe surgery so that the normal brain tissues should not be harmed. If this information is available before the surgery, the problems could be minimized. 3-D printing of tumors extracted from medical images also had an inbuilt problem of STL error. The surface models obtained from the software are not 3-D printing ready and have multiple errors such as holes, the inverted orientation of triangles, shells, and border edges. Because of such errors in the STL mesh, faulty or erroneous 3-D printed parts get produced. If such parts are used by the neurosurgeons for preoperative planning of surgery the normal healthy tissues of the brain could permanently get damaged and will harm the normal functioning of the patient and in the worst-case scenario could be life-threatening to the patient. To avoid such problems an attempt has been made in the present study. Medical imaging (MRI) datasets of brain tumors are used to create 3-D printed brain tumors. For extracting the tumor from images an open-source software, 3-D slicer has been used. The surface models directly obtained from the 3-D slicer are then optimized for errors in Autodesk NetFabb software. The surface models before and after optimization are 3-D printed using Makerbot Replicator 3-D printer and are compared. The comparison showed that the physical models directly printed from the surface models obtained from 3-D slicer are missing important information regarding tumor exact size and shape. The optimized surface models obtained from Autodesk Netfabb are having refined mesh with STL errors minimized and thus the physical models printed from these surface models are more accurate and are preserving the exact shape and size of the tumor. © 2022, The Institution of Engineers (India).