Over 340,000 people in the US have surgery to correct nasal airway obstruction (NAO) annually. Approximately 23-37% of these surgeries fail to correct patients'symptoms. The high inefficacy rate of nasal surgery is largely due to the lack of tools that can reliably quantify nasal function and predict surgical outcomes. Computational methods for quantifying nasal function show significant promise, but information is lacking on which biophysical variables best predict symptom changes, what ranges of objective values are normative, and how best to make a virtual surgery tool that surgeons can use to develop the """"""""correct"""""""" surgical plan for each individual. During the past four years, we explored computational fluid dynamics (CFD) modeling as a potential basis for this tool. We created pre- and post-surgery databases of NAO patient surveys, computed tomography (CT) scan-based CFD models, and computed objective measures of nasal surgical outcomes. We found that certain CFD biophysical variables - nasal resistance, heat flux, and unilateral airflow - discriminated between pre- and post-surgery states and correlated best with patient-reported symptoms. We also found that virtual surgery CFD models that attempted to replicate the actual surgery produced CFD-based measurements similar to those based on actual surgery models, thus providing the initial validation that virtual surgery planning is feasible. Our long-term goal is o develop a nasal virtual surgery tool that will be universally accessible to clinicians to improve patient outcomes. This goal will be accomplished in a stepwise fashion. The first step, identifying biophysical variables that track with patient symptoms, was accomplished by our prior study. The second step, which is the goal of this proposal for renewal, is to determine normative values for these variables as targets for surgery, develop methods to optimize virtual nasal surgery, and to explore the impact of virtual surgery modeling on surgeon decision-making. Future steps will include the creation of user-friendly virtual surgery software for the clinician and a prospective clinical trial to determine if virtual planning-guided surgeries are moe successful than the current standard of care. Our central hypothesis is that the current standard of care for NAO surgery can be improved by using a virtual surgery tool to design individualized nasal anatomy that optimizes nasal function by targeting the correct type and amount of surgery.

Public Health Relevance

More than 340,000 people in the US have surgery to fix nasal airway obstruction every year, yet up to half of these surgeries don't help the patients'symptoms. Recently, using computer models to estimate the outcomes of nasal surgery (i.e. virtual surgery) has shown great promise, but more information is needed before these can be explored on a larger scale. This project aims to add important information about these models that may be used as a tool to help doctors customize each surgery, resulting in improved surgical outcomes. 1

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Research Project (R01)
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Biomedical Computing and Health Informatics Study Section (BCHI)
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Peng, Grace
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Medical College of Wisconsin
Schools of Medicine
United States
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