Estimating Maxillary Sinus Volume Using Smartphone Camera - Christoforos Meliadis; Emily Feng; Ezekiel Johnson; Wendy Zhu; Paramesh Gopi; Vivek Mohan; Peter H. Hwang; Jacob Johnson; Bryant Y. Lin (IEEE Open Journal of Engineering in Medicine and Biology)
Goal: This study aims to introduce a novel method for estimating maxillary sinus volume using smartphone technology, providing an accessible alternative to traditional imaging techniques. Methods: We recruited 40 participants to conduct a comparative analysis between Computed Tomography (CT) and face scans obtained using an Apple iPhone. Utilizing Apple's ARKit for 3D facial mesh modeling, we estimated sinus dimensions based on established craniofacial landmarks and calculated the volume through a geometric approximation of the maxillary sinus. Results: We demonstrated a high degree of agreement between CT and face scans, with Mean Absolute Percentage Errors (MAPE) of 8.006 ± 8.839% (Width), 6.725 ± 4.595% (Height), 9.952 ± 6.733% (Depth), and 10.429 ± 7.409% (Volume). These results suggest the feasibility of this non-invasive approach for clinical use. Conclusions: This method aligns with the growing focus on telemedicine, presenting significant reductions in healthcare costs and radiation exposure from CT scans. It marks a substantial advancement in otolaryngology and maxillofacial surgery, showcasing the integration of smartphone technology in medical diagnostics and opening avenues for innovative, patient-friendly, and cost-effective healthcare solutions.