|About this Abstract
||MS&T23: Materials Science & Technology
||Leveraging Integrated Computational Materials Engineering for High-fidelity Physics-based and Machine Learning Models
||Robotic Bending of Craniomaxillofacial Graft Fixation Plates
||Brian Patrick Thurston, Javier Vazquez-Armendariz, Luis Olivas-Alanis, Tobias Mahan, Ciro Rodriguez, Michael Groeber, Stephen Niezgoda, Hany Emam, Roman Skoracki, Jian Cao, Glenn Daehn, David Dean
|On-Site Speaker (Planned)
||Brian Patrick Thurston
Large craniomaxillofacial (CMF) fixation plates may be needed within a few days to a week in cases of trauma or advanced stage cancer. While these plates can be 3D printed, the standard-of-care procedure is for the attending surgeon to manually bend an off-the-shelf Ti6V4Al CMF graft fixation plate to fit a patient’s 3D printed model derived from a virtual surgical planning session. The manual bending operation may result in a plate that does not fit the underlying bone well (i.e., there may be small gaps). In addition, repeated bending may introduce damage, reducing the plate´s fatigue life. Our group has developed a treatment planning and fixation plate design software that also integrates a fabrication process to instruct a robotic system to shape fixation plates with an orderly sequence of bending and twisting operations that provide good fit and enhanced material properties.