Discipline: Biological Sciences
Subcategory: Physiology and Health
Session: 4
Room: Exhibit Hall
Sarah Gonu - College of Dupage
Additive manufacturing, also used interchangeably with 3D printing and rapid prototyping, is utilized in many industries to manufacture objects for consumer use. It is beneficial to the medical field as it can be applied to make educational tools for healthcare students and patients with life-threatening conditions. Insight is also provided with patient-specific medical aids such as implants, prosthetics, and bio-manufactured organs. There is a streamlined process in constructing patient-derived 3D models from DICOM (Digital Imaging and Communications in Medicine) files. The DICOM files were retrieved from The Cancer Imaging Archive (TCIA) through the NBIA Data Retriever and downloaded onto a device. There was, however, a challenge in converting DICOM files into rapid prototyping compatibles. With only basic anatomical knowledge and familiarity with radiographic scans, the segmentation portion proved difficult. The software used for conversion was Mimics Research 19.0 from Materialize. DICOM images were uploaded onto the software, and segmentation of a particular body part was performed. Following thorough segmentation, exportation as an STL (Standard Tessellation Language) file was accomplished. Once converted, a certain manufacturing method was applied, and the model was then printed using a selected material (e.g. polymers, ceramics, and metals) to be ultimately used according to one of the indications listed above. In this case, the prototypes are a spine (hard tissue), a kidney model (soft tissue), and an angiotensinogen protein model used for educational purposes.
Funder Acknowledgement(s): National Science Foundation under Grant No. EEC–2045738.
Faculty Advisor: Dr. Subha Kumpaty, kumpaty@msoe.edu
Role: I contributed to this research by looking through DICOM files and finding an appropriate scan. I also used Mimics Research 19.0 from Materialize to segment the spine out of a pediatric CT scan. I then converted the file into a Standard Tessellation Language format.