Reverse Engineering and Prototyping of a Nasal Cavity Model for Odorant Detection Experiments

Abstract Reverse engineering (RE) is an evolving discipline in information science that offers computer-based reproductions of components, products, or even anatomical structures. Focusing on the human nose, various approaches, including basic 3D scanning, silicone rubber impressions, or medical imaging techniques, have been used for acquisition. Among these, just imaging techniques such as CT and MRI allow us to completely visualize the internal anatomy of the nose, also enabling three-dimensional reconstructions. Based on these considerations, this work aims to create an accurate 3D reconstruction of the nose, with a special focus on the nasal cavity, starting from a preoperative CT scan dataset. A thresholding-based segmentation approach was chosen to derive the inner volume occupied by the air. From this, a constant-thickness wall was generated with a hollowing operation. After further design modifications and improvements, the assembly was 3D printed with a stereolithography machine. The obtained model was then integrated into an experimental setup, including an odor sensor and a vacuum pump to generate airflow. Preliminary tests were run to evaluate the effectiveness of the proposed solution in guaranteeing signal detection. As a preliminary output, this study showed the feasibility of an experimental workbench to replicate human sniff. This was successfully tested with odorant molecules and an odor sensor. Now, more extensive tests will have to be conducted, even comparing results with those from numerical simulation.