Modeling the effect of tumor compression on airflow dynamics in trachea using contact simulation and CFD analysis.

Malignant central airway obstruction can cause severe breathing difficulty in a patient that requires surgical intervention or stent implantation to alleviate it. A predictive model to identify the onset of this event as the central airway is progressively compressed by tumor growth will be helpful for clinicians to plan for medical intervention. We present such a model to simulate tumor compression of the trachea and the resulting change in airflow dynamics to estimate the level of stenosis that will cause severe breathing difficulties. A patient-specific model of trachea was generated from acquired Computed Tomography (CT) scans for the simulations. The compression of this trachea due to tumor growth is modeled using nonlinear contact simulations of ellipsoidal tumors with the trachea. Computational fluid dynamics (CFD) is employed to simulate the turbulent airflow during inhalation in the stenosed trachea. From the CFD simulated flow fields, the power loss due to airflow through the domain is calculated. The results show that when the obstruction in the trachea reaches 50%, compared to the undeformed model, the power loss can rise to more than 66%. A measure of breathing difficulty can be derived by correlating it with the power loss. Thus, medical intervention can be predicted based on the degree of stenosis if the induced power loss exceeds a threshold that causes severe breathing discomfort.

A Two-Scale Multi-Resolution Topologically Optimized Multi-Material Design of 3D Printed Craniofacial Bone Implants.

Bone replacement implants for craniofacial reconstruction require to provide an adequate structural foundation to withstand the physiological loading. With recent advances in 3D printing technology in place of bone grafts using autologous tissues, patient-specific additively manufactured implants are being established as suitable alternates. Since the stress distribution of these structures is complicated, efficient design techniques, such as topology optimization, can deliver optimized designs with enhanced functionality. In this work, a two-scale topology optimization approach is proposed that provides multi-material designs for both macrostructures and microstructures. In the first stage, a multi-resolution topology optimization approach is used to produce multi-material designs with maximum stiffness. Then, a microstructure with a desired property supplants the solid domain. This is beneficial for bone implant design since, in addition to imparting the desired functional property to the design, it also introduces porosity. To show the efficacy of the technique, four different large craniofacial defects due to maxillectomy are considered, and their respective implant designs with multi-materials are shown. These designs show good potential in developing patient-specific optimized designs suitable for additive manufacturing.