Virtual surgery study of changes in nasal aerodynamics after inferior turbinate reduction in patients with nasal obstruction Azadeh A.T. Borojeni, PhD,1,2 Dennis O. Frank-Ito, PhD,3,4 Julia S. Kimbell, PhD,5 John S. Rhee, MD, MPH,1 Guilherme J.M. Garcia, PhD 1,2 1 Department of Otolaryngology and Communication Sciences, and 2 Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI 3 Division of Head and Neck Surgery & Communication Sciences, and 4 Computational Biology & Bioinformatics Program, Duke University, Durham, NC, 5 Department of Otolaryngology/Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill, NC Septoplasty and turbinectomy were carried out on the post-surgery model. BACKGROUND VIRTUAL SURGERY MODELS Inferior turbinate reduction (ITR) is one of the most common surgeries to treat nasal airway obstruction (NAO). Currently, surgeons lack a tool to predict how surgical changes in nasal anatomy will affect nasal airflow. In theory, virtual surgery performed in 3-dimensional patient-specific models of the nasal anatomy combined with computational fluid dynamics (CFD) simulations can be used to predict surgical outcomes. However, standard methods do not exist to perform virtual ITR. RESULTS Bilateral nasal resistance decreased from 0.14 ± 0.11 Pa.s/ml pre-surgery to 0.085 ± 0.047 Pa.s/ml after virtual bilateral ITR. This decrease in nasal resistance was associated with an increase in total nasal airflow from 12.8 ± 4.0 L/min pre-surgery to 17.9 ± 3.2 L/min after virtual ITR. Inspiratory heat loss increased to 408 ± 60 W/m² after virtual ITR as compared to 323 ± 79 W/m² pre-surgery. These results are consistent with in vivo measurements in NAO patients undergoing ITR. One literature review article reported that ITR increases nasal airflow by 30% to 80% in the first 12 months after surgery, depending on the surgical technique used.1 In addition, CFD variables in our virtual bilateral ITR models were similar to values reported for healthy individuals in the literature.2 PRE-SURGERY NASAL PASSAGE MASK 2-PIXEL FULL LENGTH BILATERAL TURBINECTOMY BILATERAL VIRTUAL SURGERY Figure 1. Creation of virtual full-length inferior turbinectomy. The airspace mask was dilated on the left cavitiy. This process was repeated to create virtual turbinectomy on the right side. METHODS Comparison of bilateral virtual inferior turbinate reduction (ITR) results with the post-surgery outcomes Bilateral Flow (L/min) Nasal Resistance (Pa.s/mL) Heat Flux (W/m2) Three-dimensional models of the human nasal cavity were created from pre-surgery CT scans of five NAO patients using the medical imaging software MimicsTM. Bilateral virtual ITR was performed in MimicsTM by trimming a 2-pixel layer of tissue (~ 0.8 mm) around the left and right inferior turbinates along the entire length of the turbinate. Steady-state inspiratory airflow simulations were conducted in both the pre-surgery and virtual ITR models with a fixed transnasal pressure gradient before and after surgery. CFD variables related to nasal function such as flowrate, nasal resistance, airflow partitioning between left and right nostrils, and inspiratory heat loss were quantified. 408 ± 60 422 ± 47.5 17.9 ± 3.2 16.6 ± 1.8 12.8 ± 4.0 CONCLUSIONS Our virtual ITR technique predicts surgical changes in nasal airflow that are consistent with in vivo measurements in NAO patients. Virtual surgery planning has the potential to become a useful tool for surgeons interested in optimizing outcomes after nasal surgery.   PRE - SURGERY BILATERAL – VIRTUAL ITR POST - SURGERY PRE - SURGERY BILATERAL – VIRTUAL ITR POST - SURGERY PRE - SURGERY BILATERAL – VIRTUAL ITR POST - SURGERY Figure 2. Comparison of virtual turbinectomy effect of objective variables before and after creating the turbinate reduction on the most and least obstructed sides. REFERENCES ACKNOWLEDGEMENT 1 Leong S.C. and Eccles R. ‘Inferior turbinate surgery and nasal airflow: evidence-based management’ Curr Opin Otolaryngol Head Neck Surg 2010, 18:54–59.   2 Zhao K. and Jiang J. ‘What is normal nasal airflow? A computational study of 22 healthy adults’ International Forum of Allergy & Rhinology 2014, 4(6):435-446. We gratefully acknowledge NIH funding via grant R01EB009557 from the National Institute of Biomedical Imaging and Bioengineering.